Table of Contents

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Only IBD Data

Libraries

---

# general libraries
import pandas as pd
import numpy as np
import itertools
import scipy.stats as stats
import random
import statistics
import datetime
import re
import json

# data cleaning libraries
from collections import Counter
# !pip install smote-variants
import smote_variants
from imblearn.over_sampling import SMOTE
from sklearn.feature_selection import SelectKBest, mutual_info_classif, chi2
from sklearn.preprocessing import LabelEncoder, OrdinalEncoder, MinMaxScaler, MaxAbsScaler

# ML libraries
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score, roc_auc_score, confusion_matrix, classification_report
from sklearn.model_selection import KFold, train_test_split
from sklearn.naive_bayes import GaussianNB
from sklearn.neighbors import KNeighborsClassifier
from sklearn.neural_network import MLPClassifier
from sklearn.svm import SVC
from sklearn.tree import DecisionTreeClassifier

# Visualization libraries
from matplotlib import pyplot
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.express as px

now = datetime.datetime.now()
print ("Current date and time : ")
print (now.strftime("%Y-%m-%d %H:%M:%S"))

Current date and time : 
2021-06-04 17:26:25

Data

---

# toggle to hide code
from IPython.display import HTML

HTML('''<script>
code_show=true; 
function code_toggle() {
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 $('div.input').hide();
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$( document ).ready(code_toggle);
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<form action="javascript:code_toggle()"><input type="submit" value="Click here to toggle on/off the raw code."></form>''')

# center all images
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=True)
HTML("""
<style>
.output_png {
    display: table-cell;
    text-align: center;
    vertical-align: middle;
}
</style>
""")

Pull in Data

ENDSC Data

# all cases
all_cases = pd.read_excel("../Data/dataset/ENDOSC_1.xls", sheet_name="All cases")
# cleaned cases
cleaned_cases = pd.read_excel("../Data/dataset/ENDOSC_1_2_2.xls", sheet_name="All IBD")
cleaned_cases_og = cleaned_cases
cleaned_cases.head()

	Year	Lab No	Age	Sex	Active inflammation?	Mucosal surface	Crypt architecture	Crypt profiles	Increased lamina propria cellularity?	Mild & superficial increase in lamina propria cellularity?	...	Mucin depletion	Intraepithelial lymphocytes	Subepithelial collagen	Lamina propria granulomas	Submucosal granulomas	Basal histiocytic cells	Confirmed diagnosis	Method of confirmation	Initial pathologists diagnosis	Observing pathologists diagnosis
0	90	8989	52.410959	1	0	0	2	5	1	0	...	0	0	0	0	0	0	UC	Endoscopy	IBD ?UC	Chronic idiopathic IBD - indeterminate
1	92	10640	24.673973	1	1	0	0	7	1	0	...	2	0	0	0	0	0	Crohns	Resection	IBD indeterminate, active	Chronic idiopathic IBD - highly suggestive of ...
2	92	7489	51.345205	0	1	0	1	7	1	0	...	2	0	0	0	0	0	Crohns	Endoscopy	IBD ?Crohns	Chronic idiopathic IBD - highly suggestive of ...
3	91	8691	48.556164	1	1	0	2	6	1	0	...	0	0	0	0	0	0	UC	Resection	IBD indeterminate, active	Chronic idiopathic IBD - indeterminate
4	90	14201	39.367123	0	0	0	0	7	0	0	...	0	1	0	0	0	0	Crohns	Endoscopy	Non-specific inflammation, acute	Normal

5 rows × 29 columns

Data Definitions

# IBD_def = pd.read_excel("../Data/Column_Definitions.xlsx", sheet_name="IBD")

# IBD_def[["Data Column", "Definition", "In depth understanding"]]

cleaned_cases = cleaned_cases.drop(['Year', 'Lab No', 'Method of confirmation', 'Initial pathologists diagnosis', 'Observing pathologists diagnosis'],axis=1)

Data Manipulation

IBD Stages: Since the stages of UC is determined by the severity of symptoms, the classes are manually added based on symptoms.

Use decision trees to determine

Perhaps find a doctor who can provide some expertise into the stages? - check if this is possible (we would need multiple people to have statistically significance)

Data Transformation Since the data is already dummy coded, the transformation of it will be required for understanding the outcome after modeling.

transform_dict = [{"data":["Mucin depletion", "Crypt architecture"], 
                   "definitions":[{
                       0: "Normal",
                       1: "Mild", 
                       2: "Moderate", 
                       3: "Severe"}]},
                  {"data": ["Cryptitis extent", "Crypt abscesses extent"],
                   "definitions": [{
                       0: "None",
                       1: "Little", 
                       2: "Moderate", 
                       3: "Marked"}]},
                  {"data": ["Lamina propria polymorphs"],
                  "definitions": [{
                      0: "Absent", 
                      1: "Focal", 
                      2: "Diffuse"}]},
                  {"data": ["Cryptitis polymorphs", "Crypt abscesses polymorphs"],
                   "definitions": [{
                       0: "None",
                       1: "Few", 
                       2: "Several", 
                       3: "Many"}]},
                  {"data": ["Epithelial changes"], 
                   "definitions": [{
                       0: "Normal",
                       1: "Flattening ",
                       2:  "Degeneration", 
                       3: "Erosion"}]},
                  {"data": ["Mucosal surface"], 
                   "definitions": [{
                       0: "Flat",
                       1: "Irregular", 
                       2: "Villous projections"}]}]

Set Seed for consistency

random.seed(123)

Crypt architecture measures the severity of the deformation of the colon, which will also signify at what severity stage the cases are at. This is the column that will be used for determining cases severities.

cleaned_cases['Crypt architecture'].unique()

crypt_dict = {0:"normal",
              1:"mild",
              2:"moderate",
              3:"severe"}

cleaned_cases['Severity of Crypt Arch'] = [crypt_dict[x] for x in cleaned_cases['Crypt architecture']]

'Severity of Crypt Arch' + 'diagnoses'

'Severity of Crypt Archdiagnoses'

convert data to object rather than int since these are categorical data.

def change_to_object(df, data_col):
    df[data_col] = df[data_col].astype(object)

run = [change_to_object(cleaned_cases, c) for c in cleaned_cases.columns[3:]]
cleaned_cases['Crypt profiles'] = cleaned_cases['Crypt profiles'].astype('int')
cleaned_cases.dtypes

Age                                                             float64
Sex                                                               int64
Active inflammation?                                              int64
Mucosal surface                                                  object
Crypt architecture                                               object
Crypt profiles                                                    int32
Increased lamina propria cellularity?                            object
Mild & superficial increase in lamina propria cellularity?       object
Increased lymphoid aggregates in lamina propria?                 object
Patchy lamina propria cellularity?                               object
Marked & transmucosal increase in lamina propria cellularity     object
Cryptitis extent                                                 object
Cryptitis polymorphs                                             object
Crypt abscesses extent                                           object
Crypt abscesses polymorphs                                       object
Lamina propria polymorphs                                        object
Epithelial changes                                               object
Mucin depletion                                                  object
Intraepithelial lymphocytes                                      object
Subepithelial collagen                                           object
Lamina propria granulomas                                        object
Submucosal granulomas                                            object
Basal histiocytic cells                                          object
Confirmed diagnosis                                              object
Severity of Crypt Arch                                           object
dtype: object

Data Cleaning

Clean Diagnosis: Strip data and Upper Case and ensure spelling of all are correct to prevent any separation of classes which are unnecessary.

print(cleaned_cases['Confirmed diagnosis'].unique())
cleaned_cases['Confirmed diagnosis'] = [c.strip().upper() for c in cleaned_cases['Confirmed diagnosis']]
print( cleaned_cases['Confirmed diagnosis'].unique())

['UC' 'Crohns' 'Crohns ' 'Uc']
['UC' 'CROHNS']

#cleaned_cases.columns
#cleaned_cases["Method of confirmation"] = [x if x != "Endosocpy" else "Endoscopy" for x in cleaned_cases["Method of confirmation"]]
#cleaned_cases["Method of confirmation"].unique()

#cleaned_cases['Observing pathologists diagnosis'].unique()

#cleaned_cases['Initial pathologists diagnosis'].unique()
#cleaned_cases['Initial pathologists diagnosis'] = [d if d != "IBD ?Crohn's" else "IBD ?Crohns" for d in cleaned_cases['Initial pathologists diagnosis']]
#cleaned_cases['Initial pathologists diagnosis'] = [d if d not in ["Non-specific inflammation,chronic", "Non-specific inflammaton, chronic"] else "Non-specific inflammation, chronic" for d in cleaned_cases['Initial pathologists diagnosis']]
#cleaned_cases['Initial pathologists diagnosis'].sort_values().unique()

#cleaned_cases['Year'].sort_values().unique()

Missing/Duplicate Data Checks

There is no duplicates data

print(f'IBD duplicates: {cleaned_cases.duplicated().any()}')

IBD duplicates: True

There are no missing data values

print(f'IBD missing: {cleaned_cases.isnull().values.any()}')

IBD missing: False

Train Test Split

Cross and coworkers randomly shuffled the dataset and split the first 540 cases as the train set and the lasts 269 cases as the test set.

X = cleaned_cases.drop('Confirmed diagnosis',axis=1)
y = cleaned_cases['Confirmed diagnosis']
X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=269, random_state=123)
print(f'Train set has {X_train.shape[0]} rows and test set has {X_test.shape[0]} rows')

Train set has 375 rows and test set has 269 rows

Class Imbalance

The minority class of heatlhy was oversampled so that there were equal diseased as unhealthy classes. This is also reflected in graphs below.

Counter(y_train)

Counter({'UC': 285, 'CROHNS': 90})

#Counter(cleaned_cases['Initial pathologists diagnosis'])

EDA

Jamie

---

The age is skewed towards the younger generations, and there are outliers of age under 15 and above 85. Since there is no proof that these age groups are errors opposed to only having a low count, they will be left in the data.

plt.figure(figsize=(10,10))
sns.distplot(cleaned_cases.Age.values, bins=50, kde=True)
plt.xlabel('Age', fontsize=12)
plt.show()

C:\ProgramData\Anaconda\lib\site-packages\seaborn\distributions.py:2557: FutureWarning:

`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).

The data below shows that majority of the cases are from years 90-92 and 95-96. The other years have minimal contribution for years prior to year 90.

#plt.figure(figsize=(10,10))
#sns.distplot(cleaned_cases.Year.values, bins=50, kde=True)
#plt.xlabel('Year', fontsize=12)
#plt.show()

While the data is a mixture of both histology and endoscopy, but majority of the confirmation methods are endoscopy.

fig = px.histogram(cleaned_cases, x="Age", color='Sex')
fig.show()

Distribution of the dataset, where majority of the classes are UC and the remaining are split to normal and UC roughly evenly.

cd_gb = cleaned_cases.groupby("Confirmed diagnosis").count().reset_index()
fig = px.bar(cd_gb, x='Confirmed diagnosis', y='Sex')
fig.show()
# cd_gb

fig = px.histogram(cleaned_cases, x="Age", color='Confirmed diagnosis')
fig.show()
plt.figure(figsize=(10,10))

<Figure size 720x720 with 0 Axes>

<Figure size 720x720 with 0 Axes>

correlations

The correlation matrix is show below, which is no the same method which is used for continuous variable, but rather categorical variables.

corr_matrix = cleaned_cases.apply(lambda x : pd.factorize(x)[0]).corr(method='pearson', min_periods=1)
corr_matrix.head()

	Age	Sex	Active inflammation?	Mucosal surface	Crypt architecture	Crypt profiles	Increased lamina propria cellularity?	Mild & superficial increase in lamina propria cellularity?	Increased lymphoid aggregates in lamina propria?	Patchy lamina propria cellularity?	...	Lamina propria polymorphs	Epithelial changes	Mucin depletion	Intraepithelial lymphocytes	Subepithelial collagen	Lamina propria granulomas	Submucosal granulomas	Basal histiocytic cells	Confirmed diagnosis	Severity of Crypt Arch
Age	1.000000	-0.024630	0.000645	0.066984	0.024193	-0.013297	0.025116	-0.014794	0.030832	0.030682	...	0.009706	-0.005371	-0.017000	-0.014212	NaN	-0.015907	-0.019861	0.055083	-0.015878	0.024193
Sex	-0.024630	1.000000	0.012179	0.105066	0.000677	0.035672	-0.001894	0.011948	0.010158	-0.012239	...	-0.007131	-0.005653	0.059029	-0.033380	NaN	-0.004193	-0.006338	0.040239	-0.113294	0.000677
Active inflammation?	0.000645	0.012179	1.000000	0.281825	0.066631	0.136076	-0.694303	0.076122	0.320400	0.419807	...	0.900782	0.526095	0.575044	-0.044335	NaN	0.097917	0.018071	0.104854	-0.079975	0.066631
Mucosal surface	0.066984	0.105066	0.281825	1.000000	-0.060980	0.166125	-0.278963	-0.059369	0.025034	-0.067872	...	0.191447	0.228068	0.310093	-0.026130	NaN	-0.051666	-0.040136	0.023768	-0.229855	-0.060980
Crypt architecture	0.024193	0.000677	0.066631	-0.060980	1.000000	0.131529	-0.129055	-0.025416	-0.104277	0.071958	...	0.088256	0.076395	0.107059	-0.004681	NaN	0.038857	0.032759	-0.007064	-0.010103	1.000000

5 rows × 25 columns

We see strong correlations between the symptoms. Specifically, there is a strong correlation between active inflammation and lamina propria polymorphs, which is investigated further below.

Many of the correlations are intuitively connected. For example, cryptis polymorphs and extent, since they are both related to the the fact of where there is inflammation in the linings of the stomach to the morphed cells of the glands.

One interesting obervation is the correlation of epithelial changes and the mucin depletions since the epithelial layer concerns the outter layer of the intestine and the mucin depletion primarily concerns with the inner side of the organ.

fig = px.imshow(corr_matrix)
fig.update_yaxes(visible=False, showticklabels=False)
fig.update_xaxes(visible=False, showticklabels=False)
fig.show()

Active inflammation and lamina propria polymorphs

Overall, the active inflamation makes sense considering if there is no inflammation, that there in turn would have no polymorphs. Since the inner linings are typically only shows to morph when there is inflammation, this is intuitive in the results.

sns.stripplot(x='Active inflammation?', y='Lamina propria polymorphs', data=cleaned_cases, jitter=True)
sns.despine()

%%time
sns.pairplot(cleaned_cases)

Wall time: 1min 36s

<seaborn.axisgrid.PairGrid at 0x22ada860400>

Odds Ratio

Odds ratio is a measure of association between an exposure and an outcome. The OR represents the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure. source

There is no strong correlations between the two, that if a patient is of a specified year and age, there is a 1:1 ratio of the patient being diagnosed with UC of chrohns.

# odds ratio calc
uc_ch = cleaned_cases.loc[cleaned_cases["Confirmed diagnosis"].isin(['UC', 'CROHNS'])]
table_uc = uc_ch[["Confirmed diagnosis", "Sex", "Active inflammation?"]].groupby("Confirmed diagnosis").sum()#.values
print(table_uc)
oddsratio_uc, pvalue_uc = stats.fisher_exact(table_uc)
print("OddsR: ", round(oddsratio_uc,4), "p-Value:", pvalue_uc)

                     Sex  Active inflammation?
Confirmed diagnosis                           
CROHNS                96                    87
UC                   205                   283
OddsR:  1.5233 p-Value: 0.01851111505184613

Reducing categorical classes Since there isn't a high number of classes in each categorical columns, there is no need to reduce the number of classes in a categorical set.

Walter

---

Each column in the dataset is a symptom. SOme of the symptoms are rankings. When the column for Subepithelial collagen is 1 it means that the patient had that symptom and when it is 0 it means the patient did not have that symptom.

train = pd.concat([X_train,y_train],axis=1)

Supervised Learning

Get only the binary variables

binary_vars = X_train.columns[X_train.apply(lambda series: False if set(series)-{0,1} else True)]
binary_vars = list(set(binary_vars) - set(['Active inflammation?']))
# binary_vars

Calculate the relative risk ratio of having IBD if patient has or doesnt have Patchy lamina propria cellularity

patchyVsIbd   = train.groupby(['Patchy lamina propria cellularity?','Confirmed diagnosis']).size()
patchySummary = X_train.groupby('Patchy lamina propria cellularity?').size()
print(patchyVsIbd)
print(patchySummary)

Patchy lamina propria cellularity?  Confirmed diagnosis
0                                   CROHNS                  63
                                    UC                     231
1                                   CROHNS                  27
                                    UC                      54
dtype: int64
Patchy lamina propria cellularity?
0    294
1     81
dtype: int64

What proportion of those with patchy lamina propria had Crohn's Disease?

proportions = patchyVsIbd/patchySummary
proportions

Patchy lamina propria cellularity?  Confirmed diagnosis
0                                   CROHNS                 0.214286
                                    UC                     0.785714
1                                   CROHNS                 0.333333
                                    UC                     0.666667
dtype: float64

How much more chance of getting Crohn's disease if you have patchy lamina propria cellularity VS if you dont have patch lamina prpria cellularity?

proportions.loc[1]/proportions.loc[0]

Confirmed diagnosis
CROHNS    1.555556
UC        0.848485
dtype: float64

Observe above that the probabilit of getting Crohn's is twice as much if you have patchy lamina propria cellularity VS if you dont have patchy lamina.

Determine relative risk of Crohn's or UC for all the symptoms
Calculation will require creating 3 tables:

1. Symptom, Is Symptom Present, Confirmed Diagnosis, Count
2. Symptom, Is Symptom Present, Count
3. Symptom, Is Symptom Present, Confirmed Diagnosis, Proportion
4. Symptom, Confirmed Diagnosis, Relative Risk (Final Table)

#1.Symptom, Is Symptom Present, Confirmed Diagnosis, Count
#Column, Value, Value for Diagnosis Column
binaryTrain = train[binary_vars+['Confirmed diagnosis']]
symptomDiagnosis = binaryTrain.reset_index().melt(id_vars=['index','Confirmed diagnosis'])
#Column, Value, Value for Diagnosis Column, Count
diseaseCountPerSymptom = symptomDiagnosis.groupby(['variable','value','Confirmed diagnosis']).size()
diseaseCountPerSymptom.head()

variable                               value  Confirmed diagnosis
Basal histiocytic cells                0      CROHNS                  86
                                              UC                     269
                                       1      CROHNS                   4
                                              UC                      16
Increased lamina propria cellularity?  0      CROHNS                  36
dtype: int64

#2.Symptom, Is Symptom Present, Count
countPerSymptom = symptomDiagnosis.groupby(['variable','value']).size()
countPerSymptom.head()

variable                                          value
Basal histiocytic cells                           0        355
                                                  1         20
Increased lamina propria cellularity?             0        103
                                                  1        272
Increased lymphoid aggregates in lamina propria?  0        307
dtype: int64

#3. Symptom, Is Symptom Present, Confirmed Diagnosis, Proportion
proportionIbdPerSymptom = diseaseCountPerSymptom/countPerSymptom
proportionIbdPerSymptom.head()

variable                               value  Confirmed diagnosis
Basal histiocytic cells                0      CROHNS                 0.242254
                                              UC                     0.757746
                                       1      CROHNS                 0.200000
                                              UC                     0.800000
Increased lamina propria cellularity?  0      CROHNS                 0.349515
dtype: float64

#4.Symptom, Confirmed Diagnosis, Relative Risk (Final Table)
propDf = proportionIbdPerSymptom.reset_index()
noSymptom  = propDf.loc[propDf['value']==0].drop('value',axis=1).set_index(['variable','Confirmed diagnosis'])
yesSymptom = propDf.loc[propDf['value']==1].drop('value',axis=1).set_index(['variable','Confirmed diagnosis'])

'''
Some symptoms such as Submucosal granulomas are only present in Crohn's pateints. this means there is no 
patient who has both submucosal granuloma and UC.  So the risk of having UC given u have submcuoal granulomas
is 0.  But currently in the yesSymptom df, the row Submucosal granulom and UC does not even exist.  So if that row 
is missing just add a row with 0
'''  
noSymptom = noSymptom.reset_index()
varDxCombos= list(itertools.product(set(noSymptom['variable']),set(noSymptom['Confirmed diagnosis'])))
allCombos  = pd.DataFrame(index=pd.MultiIndex.from_tuples(varDxCombos)) 
allCombos.index.names = ['variable','Confirmed diagnosis']
noSymptom  = noSymptom.set_index(['variable','Confirmed diagnosis'])
yesSymptom = pd.merge(yesSymptom, allCombos, left_index=True, right_index=True, how='outer').fillna({0:0})
yesSymptom.head()

		0
variable	Confirmed diagnosis
Basal histiocytic cells	CROHNS	0.200000
	UC	0.800000
Increased lamina propria cellularity?	CROHNS	0.198529
	UC	0.801471
Increased lymphoid aggregates in lamina propria?	CROHNS	0.205882

Out of all the people that had Increased lamina propria cellularity, what percent of them had Crohn's disase?
In below table see that 22.5% of patients with Increased lamina propria cellularity had Crohn's disease.

Out of all the people that did NOT have Increase lamina propria cellularity, how many had Crohn's disease?

noSymptom = pd.merge(noSymptom, allCombos, left_index=True, right_index=True, how='outer').fillna({0:0})
noSymptom.head()

		0
variable	Confirmed diagnosis
Basal histiocytic cells	CROHNS	0.242254
	UC	0.757746
Increased lamina propria cellularity?	CROHNS	0.349515
	UC	0.650485
Increased lymphoid aggregates in lamina propria?	CROHNS	0.247557

You have two people, one with increased lamina propria cellularity and the other one without increased lamina propria cellularity. How much more likely is the first person to have Crohn's disease compared to the second?

You have two people, one with increased lamina propria cellularity and the other one without increased lamina propria cellularity. How much more likely is the first person to have Crohn's disease compared to the second?

relativeRiskIbd = (yesSymptom/noSymptom).reset_index()
relativeRiskIbd.head()

	variable	Confirmed diagnosis	0
0	Basal histiocytic cells	CROHNS	0.825581
1	Basal histiocytic cells	UC	1.055762
2	Increased lamina propria cellularity?	CROHNS	0.568015
3	Increased lamina propria cellularity?	UC	1.232112
4	Increased lymphoid aggregates in lamina propria?	CROHNS	0.831656

fig,ax = plt.subplots(nrows=1,ncols=2, sharey=True)
crohns = relativeRiskIbd[relativeRiskIbd['Confirmed diagnosis']=='CROHNS']
uc     = relativeRiskIbd[relativeRiskIbd['Confirmed diagnosis']=='UC']
# normal = relativeRiskIbd[relativeRiskIbd['Confirmed diagnosis']=='NORMAL']
ax[0].barh(crohns['variable'],crohns[0])
ax[0].set(title='Crohns',
         ylabel='SYMPTOMS')
ax[1].barh(uc['variable'],uc[0])
ax[1].set(title='UC',xlabel='Relative Risk of Diagnosis Given That Patient has this Symptom',)
#ax[2].barh(normal['variable'],normal[0])
# ax[2].set(title='Normal')

[Text(0.5, 1.0, 'UC'),
 Text(0.5, 0, 'Relative Risk of Diagnosis Given That Patient has this Symptom')]

For unsupervised EDA, The objective is to find multiple symptoms that are all 1 for the same patients and are all 0 for other patients.

1. First, manually calculate the risk ratio between Symptom A and Symptom B
2. Next, create a cross tab where the row is Symptom A, the column is Symptom B and the cell value is the risk ratio of Symptom B / Symptom A
3. Finally, find the groups of symptoms that have highest risk ratios for one another. If 3 columns have high relative risk ratios, consider keeping only one of those columns and dropping the other 2

Risk Ratio

What is the risk of getting "Increased lamina propria cellularity" if you do have "Lamina propria granulomas" versus the risk of getting "Increased lamina propria cellularity" if you do not have "Lamina propria granulomas"?

If two symptoms are both positive in 1000 patients. And in another 1000 patients the two symptoms are negative. This would indicate correlation between those 2 symptoms.

exposure = 'Lamina propria granulomas'
disease  = 'Increased lamina propria cellularity?'
risks = X_train.groupby([exposure,disease]
               ).size()/X_train.groupby([exposure]).size()
risks = risks.reset_index()
riskGivenNoExposure = risks.loc[(risks[exposure] == 0)&
                              (risks[disease] == 1),0].values[0]
riskGivenExposure   = risks.loc[(risks[exposure] == 1)&
                              (risks[disease] == 1),0].values[0]
riskGivenExposure/riskGivenNoExposure

1.2046332046332047

Get the cross tab of every symptom with every other symptom

def multicolumn_crosstab(df,cols):
    cols=sorted(cols)
    dummies = pd.get_dummies(df[cols])
    dfWithDummies = pd.concat([df,dummies],axis=1)
    dfWithDummies = dfWithDummies.reset_index()
    dfMelt = dfWithDummies.melt(id_vars=np.concatenate([np.array(['index']),dummies.columns.values]),
                      value_vars=cols)
    dfMelt = dfMelt.drop('index',axis=1)
    levelGroup = dfMelt.groupby(['variable','value'])
    crosstab = levelGroup.sum()
    countPerLevel = levelGroup.size()
    crossTabProp = crosstab.divide(countPerLevel,axis=0)
    return crossTabProp

ct = multicolumn_crosstab(X_train.astype(str),binary_vars)

In the below cross tab, the value in the second row, and in the fourth column (Incerased Lamina propria cellularity_1) is the number 0.894737. This means that 89% of the patients (in the train set) had both Basal histocytic cells and Increased lamina propria cellularity. Notice how this number 89% adds up tihe the 10.5263 % on the left of it. That 10% number is the proportion of patients that had basal histocytic cells but did NOT have icnreased lamina propria cellularity.

ct.head()

		Basal histiocytic cells_0	Basal histiocytic cells_1	Increased lamina propria cellularity?_0	Increased lamina propria cellularity?_1	Increased lymphoid aggregates in lamina propria?_0	Increased lymphoid aggregates in lamina propria?_1	Intraepithelial lymphocytes_0	Intraepithelial lymphocytes_1	Lamina propria granulomas_0	Lamina propria granulomas_1	...	Marked & transmucosal increase in lamina propria cellularity_1	Mild & superficial increase in lamina propria cellularity?_0	Mild & superficial increase in lamina propria cellularity?_1	Patchy lamina propria cellularity?_0	Patchy lamina propria cellularity?_1	Sex_0	Sex_1	Subepithelial collagen_0	Submucosal granulomas_0	Submucosal granulomas_1
variable	value
Basal histiocytic cells	0	1.000000	0.000000	0.284507	0.715493	0.814085	0.185915	0.974648	0.025352	0.963380	0.036620	...	0.329577	0.991549	0.008451	0.800000	0.200000	0.523944	0.476056	1.0	0.988732	0.011268
	1	0.000000	1.000000	0.100000	0.900000	0.900000	0.100000	1.000000	0.000000	0.900000	0.100000	...	0.300000	1.000000	0.000000	0.500000	0.500000	0.750000	0.250000	1.0	1.000000	0.000000
Increased lamina propria cellularity?	0	0.980583	0.019417	1.000000	0.000000	1.000000	0.000000	0.980583	0.019417	0.980583	0.019417	...	0.000000	1.000000	0.000000	1.000000	0.000000	0.533981	0.466019	1.0	1.000000	0.000000
	1	0.933824	0.066176	0.000000	1.000000	0.750000	0.250000	0.974265	0.025735	0.952206	0.047794	...	0.452206	0.988971	0.011029	0.702206	0.297794	0.536765	0.463235	1.0	0.985294	0.014706
Increased lymphoid aggregates in lamina propria?	0	0.941368	0.058632	0.335505	0.664495	1.000000	0.000000	0.977199	0.022801	0.951140	0.048860	...	0.400651	0.990228	0.009772	0.745928	0.254072	0.537459	0.462541	1.0	0.986971	0.013029

5 rows × 21 columns

Which feature is most correlated with the other features?

Observe that "Increased lamina propria cellularity" and "Active Inflammation" are the columns that is most correlated with the other symptoms.

noExposureDf: Get all the risks of getting Symptom B given that you dont have symptom A.
exposureDf: Get all the risks of getting Symptom B given that you do have symptom A.

crossTab     = ct.reset_index()
noExposureDf = crossTab.loc[crossTab['value']=='0']
exposureDf   = crossTab.loc[crossTab['value']=='1']

Divide all the risk-given-exposure/ risk-given-no-exposure to get the relative risk for every symptom pair

noExposureDf = noExposureDf.set_index('variable').drop('value',axis=1)
exposureDf   = exposureDf.set_index('variable').drop('value',axis=1)
relativeRisks= exposureDf/noExposureDf
relativeRisks.head()

	Basal histiocytic cells_0	Basal histiocytic cells_1	Increased lamina propria cellularity?_0	Increased lamina propria cellularity?_1	Increased lymphoid aggregates in lamina propria?_0	Increased lymphoid aggregates in lamina propria?_1	Intraepithelial lymphocytes_0	Intraepithelial lymphocytes_1	Lamina propria granulomas_0	Lamina propria granulomas_1	...	Marked & transmucosal increase in lamina propria cellularity_1	Mild & superficial increase in lamina propria cellularity?_0	Mild & superficial increase in lamina propria cellularity?_1	Patchy lamina propria cellularity?_0	Patchy lamina propria cellularity?_1	Sex_0	Sex_1	Subepithelial collagen_0	Submucosal granulomas_0	Submucosal granulomas_1
variable
Basal histiocytic cells	0.000000	inf	0.351485	1.257874	1.105536	0.537879	1.026012	0.000000	0.934211	2.730769	...	0.910256	1.008523	0.0	0.625000	2.500000	1.431452	0.525148	1.0	1.011396	0.0
Increased lamina propria cellularity?	0.952315	3.408088	0.000000	inf	0.750000	inf	0.993557	1.325368	0.971061	2.461397	...	inf	0.988971	inf	0.702206	inf	1.005214	0.994026	1.0	0.985294	inf
Increased lymphoid aggregates in lamina propria?	1.031040	0.501634	0.000000	1.504902	0.000000	inf	0.993235	1.289916	1.051370	0.000000	...	0.000000	1.009868	0.0	1.281467	0.173643	0.985027	1.017399	1.0	1.013201	0.0
Intraepithelial lymphocytes	1.057803	0.000000	0.805281	1.074214	0.948889	1.232323	0.000000	inf	0.924242	2.904762	...	1.016667	1.008264	0.0	0.991870	1.029536	0.616162	1.452381	1.0	1.011050	0.0
Lamina propria granulomas	0.912281	2.666667	0.475248	1.204633	1.232877	0.000000	0.954545	3.000000	0.000000	inf	...	0.000000	1.008403	0.0	0.164384	4.588235	0.865979	1.156627	1.0	0.802228	72.0

5 rows × 21 columns

The relative risk from our risk matrix is the same as the one when we manually calculated it. 1.559171

relativeRisks.loc['Lamina propria granulomas','Increased lamina propria cellularity?_1' ]

1.2046332046332047

Replace infinity values or abnormally high Relative risks with 0

relativeRisks = relativeRisks.applymap(lambda cell:0 if cell>20 else cell)

Observe in heatmap below that Submucosal granulomas are highly correlated with lamina propria granulomas

symptomPresent = [column for column in ct.columns if '1' in column]
sns.heatmap(relativeRisks[symptomPresent])

<AxesSubplot:ylabel='variable'>

Out of the 453 patients that did not have patchy lamina propria cellularity none of those patients also had lamina propria granulomas.
However, out of the 87 patients that had patchy laminap propria cellularity, 4 of those patients also had lamina propria granulomas.
It looks like these 2 columns are correlated.

X_train.groupby(['Patchy lamina propria cellularity?','Submucosal granulomas']).size()

Patchy lamina propria cellularity?  Submucosal granulomas
0                                   0                        294
1                                   0                         77
                                    1                          4
dtype: int64

Out of the 453 patients that did not have patchy lamina propria cellularity only 1 of those patients also had lamina propria granulomas.
However, out of the 87 patients that had patchy laminap propria cellularity, 12 of those patients also had lamina propria granulomas.
It looks like these 2 columns are correlated.

X_train.groupby(['Patchy lamina propria cellularity?','Lamina propria granulomas']).size()

Patchy lamina propria cellularity?  Lamina propria granulomas
0                                   0                            292
                                    1                              2
1                                   0                             68
                                    1                             13
dtype: int64

You have two people, one with increased lamina propria cellularity and the other one without increased lamina propria cellularity. How much more likely is the first person to have Crohn's disease compared to the second?

train.groupby(['Submucosal granulomas','Confirmed diagnosis']).size()

Submucosal granulomas  Confirmed diagnosis
0                      CROHNS                  86
                       UC                     285
1                      CROHNS                   4
dtype: int64

Model Assumptions

The model assumptions for all models are not concerning to the data for visualization. The main requirement is that the data doesn't have a linear correlation between features and that the data is independent, assumed by the unique data points.

Due to the data primarily being categorical, the modifications/assumptions are difficult to decipher.

Data Prep for Modeling

Dummy coding the Data

There are two different set methods, dummy coding and ordinal. Before converting to dummy code, the data is first returned to it original form, then dummy coded to understand the effects of feature reduction and whether its required.

# convert it back to the original setup
df_reset = cleaned_cases.copy()
df_reset_od = cleaned_cases.copy()
df_reset.head()

	Age	Sex	Active inflammation?	Mucosal surface	Crypt architecture	Crypt profiles	Increased lamina propria cellularity?	Mild & superficial increase in lamina propria cellularity?	Increased lymphoid aggregates in lamina propria?	Patchy lamina propria cellularity?	...	Lamina propria polymorphs	Epithelial changes	Mucin depletion	Intraepithelial lymphocytes	Subepithelial collagen	Lamina propria granulomas	Submucosal granulomas	Basal histiocytic cells	Confirmed diagnosis	Severity of Crypt Arch
0	52.410959	1	0	0	2	5	1	0	1	0	...	0	0	0	0	0	0	0	0	UC	moderate
1	24.673973	1	1	0	0	7	1	0	0	0	...	2	0	2	0	0	0	0	0	CROHNS	normal
2	51.345205	0	1	0	1	7	1	0	0	0	...	2	3	2	0	0	0	0	0	CROHNS	mild
3	48.556164	1	1	0	2	6	1	0	0	1	...	1	0	0	0	0	0	0	0	UC	moderate
4	39.367123	0	0	0	0	7	0	0	0	0	...	0	0	0	1	0	0	0	0	CROHNS	normal

5 rows × 25 columns

transform_dict

[{'data': ['Mucin depletion', 'Crypt architecture'],
  'definitions': [{0: 'Normal', 1: 'Mild', 2: 'Moderate', 3: 'Severe'}]},
 {'data': ['Cryptitis extent', 'Crypt abscesses extent'],
  'definitions': [{0: 'None', 1: 'Little', 2: 'Moderate', 3: 'Marked'}]},
 {'data': ['Lamina propria polymorphs'],
  'definitions': [{0: 'Absent', 1: 'Focal', 2: 'Diffuse'}]},
 {'data': ['Cryptitis polymorphs', 'Crypt abscesses polymorphs'],
  'definitions': [{0: 'None', 1: 'Few', 2: 'Several', 3: 'Many'}]},
 {'data': ['Epithelial changes'],
  'definitions': [{0: 'Normal',
    1: 'Flattening ',
    2: 'Degeneration',
    3: 'Erosion'}]},
 {'data': ['Mucosal surface'],
  'definitions': [{0: 'Flat', 1: 'Irregular', 2: 'Villous projections'}]}]

for val in transform_dict:
    print("============new dictionary===========")
    cols = val['data']
    print(val['definitions'])
    for col in cols:
        try:
            df_reset[col] = [val['definitions'][0][v] for v in df_reset[col]]
        except:
            pass

============new dictionary===========
[{0: 'Normal', 1: 'Mild', 2: 'Moderate', 3: 'Severe'}]
============new dictionary===========
[{0: 'None', 1: 'Little', 2: 'Moderate', 3: 'Marked'}]
============new dictionary===========
[{0: 'Absent', 1: 'Focal', 2: 'Diffuse'}]
============new dictionary===========
[{0: 'None', 1: 'Few', 2: 'Several', 3: 'Many'}]
============new dictionary===========
[{0: 'Normal', 1: 'Flattening ', 2: 'Degeneration', 3: 'Erosion'}]
============new dictionary===========
[{0: 'Flat', 1: 'Irregular', 2: 'Villous projections'}]

# review the data transformation
df_reset[["Cryptitis extent","Cryptitis polymorphs","Crypt abscesses extent","Crypt abscesses polymorphs","Lamina propria polymorphs","Epithelial changes","Mucin depletion"]]

# get dummies
dummied = pd.get_dummies(df_reset[["Cryptitis extent","Cryptitis polymorphs","Crypt abscesses extent","Crypt abscesses polymorphs","Lamina propria polymorphs","Epithelial changes","Mucin depletion","Severity of Crypt Arch"]])
# "Method of confirmation","Initial pathologists diagnosis","Observing pathologists diagnosis", 
df_dummy = pd.merge(dummied, cleaned_cases.drop(["Cryptitis extent","Cryptitis polymorphs","Crypt abscesses extent","Crypt abscesses polymorphs","Lamina propria polymorphs","Epithelial changes","Mucin depletion", "Severity of Crypt Arch"], axis=1), how = "inner", left_index=True, right_index=True)
# "Method of confirmation","Initial pathologists diagnosis","Observing pathologists diagnosis",

df_dummy

	Cryptitis extent_Little	Cryptitis extent_Marked	Cryptitis extent_Moderate	Cryptitis extent_None	Cryptitis polymorphs_Few	Cryptitis polymorphs_Many	Cryptitis polymorphs_None	Cryptitis polymorphs_Several	Crypt abscesses extent_Little	Crypt abscesses extent_Marked	...	Mild & superficial increase in lamina propria cellularity?	Increased lymphoid aggregates in lamina propria?	Patchy lamina propria cellularity?	Marked & transmucosal increase in lamina propria cellularity	Intraepithelial lymphocytes	Subepithelial collagen	Lamina propria granulomas	Submucosal granulomas	Basal histiocytic cells	Confirmed diagnosis
0	0	0	0	1	0	0	1	0	0	0	...	0	1	0	0	0	0	0	0	0	UC
1	0	0	1	0	1	0	0	0	1	0	...	0	0	0	1	0	0	0	0	0	CROHNS
2	0	0	1	0	0	0	0	1	0	0	...	0	0	0	1	0	0	0	0	0	CROHNS
3	0	1	0	0	1	0	0	0	1	0	...	0	0	1	0	0	0	0	0	0	UC
4	0	0	0	1	0	0	1	0	0	0	...	0	0	0	0	1	0	0	0	0	CROHNS
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
639	0	0	1	0	1	0	0	0	0	0	...	0	0	0	1	0	0	0	0	1	UC
640	0	0	1	0	1	0	0	0	0	0	...	0	0	0	1	0	0	0	0	0	UC
641	1	0	0	0	1	0	0	0	1	0	...	0	0	0	1	0	0	0	0	0	UC
642	1	0	0	0	1	0	0	0	0	0	...	0	0	1	0	0	0	0	0	0	UC
643	1	0	0	0	1	0	0	0	1	0	...	0	0	1	0	0	0	0	0	0	UC

644 rows × 48 columns

for column "Initial pathologists diagnosis_?IBD ?Infective", there is only one instance of this observation. Due to this we will drop the column as it will error during analysis.

#df_dummy = df_dummy.drop(["Initial pathologists diagnosis_?IBD ?Infective","Initial pathologists diagnosis_Pouchitis", "Initial pathologists diagnosis_Diversion colitis", "Initial pathologists diagnosis_IBD indeterminate, quiescent"] ,axis=1)

df_type = pd.DataFrame(df_dummy.dtypes)

for x in df_type.loc[df_type[0] == "uint8"].reset_index()['index']:
    df_dummy[x] = df_dummy[x].astype('object')

df_dummy.dtypes

Cryptitis extent_Little                                          object
Cryptitis extent_Marked                                          object
Cryptitis extent_Moderate                                        object
Cryptitis extent_None                                            object
Cryptitis polymorphs_Few                                         object
Cryptitis polymorphs_Many                                        object
Cryptitis polymorphs_None                                        object
Cryptitis polymorphs_Several                                     object
Crypt abscesses extent_Little                                    object
Crypt abscesses extent_Marked                                    object
Crypt abscesses extent_Moderate                                  object
Crypt abscesses extent_None                                      object
Crypt abscesses polymorphs_Few                                   object
Crypt abscesses polymorphs_Many                                  object
Crypt abscesses polymorphs_None                                  object
Crypt abscesses polymorphs_Several                               object
Lamina propria polymorphs_Absent                                 object
Lamina propria polymorphs_Diffuse                                object
Lamina propria polymorphs_Focal                                  object
Epithelial changes_Degeneration                                  object
Epithelial changes_Erosion                                       object
Epithelial changes_Flattening                                    object
Epithelial changes_Normal                                        object
Mucin depletion_Mild                                             object
Mucin depletion_Moderate                                         object
Mucin depletion_Normal                                           object
Mucin depletion_Severe                                           object
Severity of Crypt Arch_mild                                      object
Severity of Crypt Arch_moderate                                  object
Severity of Crypt Arch_normal                                    object
Severity of Crypt Arch_severe                                    object
Age                                                             float64
Sex                                                               int64
Active inflammation?                                              int64
Mucosal surface                                                  object
Crypt architecture                                               object
Crypt profiles                                                    int32
Increased lamina propria cellularity?                            object
Mild & superficial increase in lamina propria cellularity?       object
Increased lymphoid aggregates in lamina propria?                 object
Patchy lamina propria cellularity?                               object
Marked & transmucosal increase in lamina propria cellularity     object
Intraepithelial lymphocytes                                      object
Subepithelial collagen                                           object
Lamina propria granulomas                                        object
Submucosal granulomas                                            object
Basal histiocytic cells                                          object
Confirmed diagnosis                                              object
dtype: object

Ordinal Data

Ordinal data is the method of which the data is already set up in. This allows the researchers to put the remaining data types into an ordinal set up for analysis.

ord_cols = ["Severity of Crypt Arch"]
# "Method of confirmation","Initial pathologists diagnosis","Observing pathologists diagnosis",

for val in ord_cols:
    print(val)
    array_un = df_reset_od[val].unique().tolist()
    df_reset_od[val] = df_reset_od[val].apply(lambda x: array_un.index(x))

Severity of Crypt Arch

df_ordinal = df_reset_od
df_ordinal.head()

	Age	Sex	Active inflammation?	Mucosal surface	Crypt architecture	Crypt profiles	Increased lamina propria cellularity?	Mild & superficial increase in lamina propria cellularity?	Increased lymphoid aggregates in lamina propria?	Patchy lamina propria cellularity?	...	Lamina propria polymorphs	Epithelial changes	Mucin depletion	Intraepithelial lymphocytes	Subepithelial collagen	Lamina propria granulomas	Submucosal granulomas	Basal histiocytic cells	Confirmed diagnosis	Severity of Crypt Arch
0	52.410959	1	0	0	2	5	1	0	1	0	...	0	0	0	0	0	0	0	0	UC	0
1	24.673973	1	1	0	0	7	1	0	0	0	...	2	0	2	0	0	0	0	0	CROHNS	1
2	51.345205	0	1	0	1	7	1	0	0	0	...	2	3	2	0	0	0	0	0	CROHNS	2
3	48.556164	1	1	0	2	6	1	0	0	1	...	1	0	0	0	0	0	0	0	UC	0
4	39.367123	0	0	0	0	7	0	0	0	0	...	0	0	0	1	0	0	0	0	CROHNS	1

5 rows × 25 columns

Of the two differing methods, one of the two will be selected for analysis.

Train/Test Split

#X_ord = df_ordinal.drop(columns=["Observing pathologists diagnosis", "Initial pathologists diagnosis", "Confirmed diagnosis"], axis=1)
X_ord = df_ordinal.drop(columns=["Confirmed diagnosis"], axis=1)
y_ord = df_ordinal['Confirmed diagnosis']

X_train_ord , X_test_ord, y_train_ord, y_test_ord = train_test_split(X_ord, y_ord, test_size=0.25, random_state=42)

X_train_ord[X_train_ord.isna().any(axis=1)]

	Age	Sex	Active inflammation?	Mucosal surface	Crypt architecture	Crypt profiles	Increased lamina propria cellularity?	Mild & superficial increase in lamina propria cellularity?	Increased lymphoid aggregates in lamina propria?	Patchy lamina propria cellularity?	...	Crypt abscesses polymorphs	Lamina propria polymorphs	Epithelial changes	Mucin depletion	Intraepithelial lymphocytes	Subepithelial collagen	Lamina propria granulomas	Submucosal granulomas	Basal histiocytic cells	Severity of Crypt Arch

0 rows × 24 columns

Max-Min Transformation

df_ord_scale = df_reset_od.drop("Confirmed diagnosis", 1)
X_train_ord = X_train_ord.copy().reset_index().drop('index',axis=1)
X_test_ord = X_test_ord.copy().reset_index().drop('index',axis=1)
for val in X_train_ord.columns:
    X_train_ord[val] = X_train_ord[val].astype(int)
    X_test_ord[val] = X_test_ord[val].astype(int)

# Scale only columns that have values greater than 1
to_scale = [col for col in X_train_ord.columns if X_train_ord[col].max() > 1]
mms = MinMaxScaler()
scaled = mms.fit_transform(X_train_ord[to_scale])
scaled = pd.DataFrame(scaled, columns=to_scale)
scaled_test = mms.fit_transform(X_test_ord[to_scale])
scaled_test = pd.DataFrame(scaled_test, columns=to_scale)

# Replace original columns with scaled ones
for col in scaled:
    X_train_ord[col] = scaled[col]
    X_test_ord[col] = scaled_test[col]
    
# df_ord_scale = X_train_ord.merge(df_reset_od["Confirmed diagnosis"], how="inner", left_index=True, right_index=True)

# X_train_ord = X_train_ord.merge(df_reset_od["Confirmed diagnosis"], how="inner", left_index=True, right_index=True)
X_train_ord[X_train_ord.isna().any(axis=1)]

	Age	Sex	Active inflammation?	Mucosal surface	Crypt architecture	Crypt profiles	Increased lamina propria cellularity?	Mild & superficial increase in lamina propria cellularity?	Increased lymphoid aggregates in lamina propria?	Patchy lamina propria cellularity?	...	Crypt abscesses polymorphs	Lamina propria polymorphs	Epithelial changes	Mucin depletion	Intraepithelial lymphocytes	Subepithelial collagen	Lamina propria granulomas	Submucosal granulomas	Basal histiocytic cells	Severity of Crypt Arch

0 rows × 24 columns

X_test_ord[X_test_ord.isna().any(axis=1)]

	Age	Sex	Active inflammation?	Mucosal surface	Crypt architecture	Crypt profiles	Increased lamina propria cellularity?	Mild & superficial increase in lamina propria cellularity?	Increased lymphoid aggregates in lamina propria?	Patchy lamina propria cellularity?	...	Crypt abscesses polymorphs	Lamina propria polymorphs	Epithelial changes	Mucin depletion	Intraepithelial lymphocytes	Subepithelial collagen	Lamina propria granulomas	Submucosal granulomas	Basal histiocytic cells	Severity of Crypt Arch

0 rows × 24 columns

SMOTE

sm = SMOTE(random_state=123)

X_sm, y_sm = sm.fit_resample(X_train_ord, y_train_ord)

print('MixMax Scaler')
print(f'''Shape of X before SMOTE: {X_ord.shape}
Shape of X after SMOTE: {X_sm.shape}''')

MixMax Scaler
Shape of X before SMOTE: (644, 24)
Shape of X after SMOTE: (706, 24)

print('\nBalance of positive and negative classes (%):')
y_sm.value_counts(normalize=True) * 100

Balance of positive and negative classes (%):

CROHNS    50.0
UC        50.0
Name: Confirmed diagnosis, dtype: float64

# Final Sets
data = [X_sm, X_test_ord, y_sm, y_test_ord]

msm = smote_variants.MSMOTE(proportion=28, random_state = 123)
X_msm, y_msm = msm.sample(X_train_ord.values, y_train_ord.values)
X_msm = pd.DataFrame(columns = X_train_ord.columns, data=X_msm)
y_msm = pd.Series(data = y_msm)
msm2 = smote_variants.MSMOTE(proportion=1, random_state = 123)
X_msm, y_msm = msm2.sample(X_msm.values, y_msm.values)
X_msm = pd.DataFrame(columns = X_train_ord.columns, data=X_msm)
y_msm = pd.Series(data = y_msm)

2021-06-04 17:31:35,375:INFO:MSMOTE: Running sampling via ('MSMOTE', "{'proportion': 28, 'n_neighbors': 5, 'n_jobs': 1, 'random_state': 123}")
2021-06-04 17:31:35,643:INFO:MSMOTE: Running sampling via ('MSMOTE', "{'proportion': 1, 'n_neighbors': 5, 'n_jobs': 1, 'random_state': 123}")

Feature Importance

Chi-squared is used for determining feature importance. source

fs = SelectKBest(score_func=chi2, k='all')
fs.fit(X_sm.to_numpy() , y_sm.to_numpy() )
X_train_fs = fs.transform(X_sm.to_numpy() )
X_test_fs = fs.transform(X_test_ord.to_numpy())

df_features = pd.DataFrame()
df_features['Features'] = X_test_ord.columns
df_features['Scores'] = np.round(fs.scores_,2)
df_features = df_features.sort_values('Scores', ascending=False)

# plot the scores
ax = sns.barplot(x="Scores", y="Features", data=df_features)

# fit the model
# data = [X_sm, X_test_ord, y_sm, y_test_ord]
model = LogisticRegression(solver='lbfgs')
t = model.fit(X_sm, y_sm)
# evaluate the model
yhat = model.predict(X_test_ord)
# evaluate predictions
accuracy = accuracy_score(y_test_ord, yhat)
print('Accuracy: %.2f' % (accuracy*100))

Accuracy: 65.22

assigned = y_sm.unique()
assigned

array(['CROHNS', 'UC'], dtype=object)

df_logit = pd.DataFrame()
df_logit['Attributes'] = X_sm.columns
for l in range(0, len(model.coef_)):
    df_logit['data_'+str(assigned[1])] = abs(model.coef_[l])
df_logit = df_logit.sort_values(by='data_UC', ascending = False)
# plot the scores
ax = sns.barplot(x="data_UC", y="Attributes", data=df_logit)

ax = sns.barplot(x="data_UC", y="Attributes", data=df_logit)

# ax = sns.barplot(x="data_NORMAL", y="Attributes", data=df_logit)

ETL PipeLine

confirmed to not be needed considering time constraint.

Machine Learning Models

---

Parameter Tuning

modelCompare = {'model': [], 'features': [], 'accuracy': [], 'f1': [], 
                'precision': [], 'recall': [], 'params': []}

def hyper_search(modelDictionary, modelParamDictionary, data, features):
    # define empty dictionaries to start
    modelAccuracy = 0
    bestModel = {}
    df_tmp = pd.DataFrame()
    modelCompare = pd.DataFrame()
    features1 = ', '.join(map(str, features))

    # iterate through the model dictionary to execute each model
    for key, value in modelDictionary.items():
        accuracyDics = {}
        finalResults = {}
        print(f'\r\nProcessing Model: {key}')

        # get the hyper parameter dictionary listings for the specific model
        paramDictionary = modelParamDictionary[key]

        # build out all permutations
        keys, values = zip(*paramDictionary.items())
        paramList = [dict(zip(keys, v)) for v in itertools.product(*values)]

        for dic in paramList:
            finalResults = main(value, data, dic)
            accuracyDics.update(groupClassifiers(finalResults))

        bestScore = 0
        avgAccuracy = 0
        plotScore = {}
        for k in accuracyDics:
            for a in accuracyDics[k][0]:
                k1 = {}
                k1 = k[:k.index('(')]
                avgAccuracy = statistics.mean(accuracyDics[k][0]['accuracy'])
                avgF1 = statistics.mean(accuracyDics[k][0]['f1'])
                avgPrecision = statistics.mean(accuracyDics[k][0]['precision'])
                avgRecall = statistics.mean(accuracyDics[k][0]['recall'])
                param = accuracyDics[k][0]['params']
                if avgAccuracy > bestScore:
                    bestScore = avgAccuracy
                    plotScore.clear()
                    plotScore = {'classifier': k1,
                                 'features': features1,
                                 'accuracy': accuracyDics[k][0]['accuracy'],
                                 'avgAccuracy': avgAccuracy,
                                 'f1': accuracyDics[k][0]['f1'],
                                 'avgF1': avgF1,
                                 'precision': accuracyDics[k][0]['precision'],
                                 'avgPrecision': avgPrecision,
                                 'recall': accuracyDics[k][0]['recall'],
                                 'avgRecall': avgRecall,
                                 'params': param}

        #plot_models(plotScore)

        df_tmp = pd.DataFrame({'model': plotScore['classifier'],
                       'features': plotScore['features'],
                       'accuracy': plotScore['avgAccuracy'],
                       'f1': plotScore['avgF1'],
                       'precision': plotScore['avgPrecision'],
                       'recall': plotScore['avgRecall'],
                       'params': plotScore['params']})
        modelCompare = modelCompare.append(df_tmp, ignore_index=True)
        df_tmp = df_tmp[0:0]
        
        print(f'*****************************************************')
        print(f'* {key}')
        print(f'* Best Params Result: ')
        print(f'* {plotScore}')
        print(f'*****************************************************')
        if bestScore > modelAccuracy:
            modelAccuracy = avgAccuracy
            bestModel.clear()
            bestModel = plotScore
    print(f'*****************************************************')
    print(f'* Best Performing Model and Params is:')
    print(f'* {bestModel}')
    print(f'*****************************************************')

    print(f'\r\n{modelCompare}')

def main(clfr, data, clfrHyperParams={}):
    X_, y_, n_folds = data
    kf = KFold(n_splits=n_folds)
    ret = {}

    for id, (trainIndex, testIndex) in enumerate(kf.split(X_, y_)):
        clf = clfr(**clfrHyperParams)
        clf.fit(X_[trainIndex], y_[trainIndex])
        pred = clf.predict(X_[testIndex])
        ret[id] = {'classifier': clf,
                   'accuracy': accuracy_score(y_[testIndex], pred),
                   'f1': f1_score(y_[testIndex], pred, average='weighted'),
                   'precision': precision_score(y_[testIndex], pred, average='micro'),
                   'recall': recall_score(y_[testIndex], pred, average='micro'),
                   'params': clf.get_params(deep=True)}

    #print(classification_report(pred, y_[testIndex]))
    return ret

def groupClassifiers(resultsDict):
    accuraccyDict = {}

    for key in resultsDict:
        c = resultsDict[key]['classifier']
        a = resultsDict[key]['accuracy']
        f = resultsDict[key]['f1']
        p = resultsDict[key]['precision']
        r = resultsDict[key]['recall']
        params = resultsDict[key]['params']
        c_ = str(c).strip()

        # Then check if the string value 'c_' exists as a key in the dictionary
        if c_ in accuraccyDict:
            accuraccyDict[c_][0]['accuracy'].append(a)
            accuraccyDict[c_][0]['f1'].append(f)
            accuraccyDict[c_][0]['precision'].append(p)
            accuraccyDict[c_][0]['recall'].append(r)
        else:
            accuraccyDict[c_] = [{'accuracy': [a], 'f1': [f], 
                                  'precision': [p], 'recall': [r],
                                  'params': [params]}]

    return(accuraccyDict)

def plot_models(accuraccyDict):
    plt.rcParams.update ({'text.usetex': False,
                                 'font.family': 'stixgeneral',
                                 'mathtext.fontset': 'stix'})
    # create a new histogram with a given dictionary key's values
    fig = plt.figure(figsize=(8, 8))
    ax = fig.add_subplot(1, 1, 1)
    plt.hist(accuraccyDict['accuracy'], facecolor='green', alpha=0.75, bins=8)
    plt.text(.20, .5, 'Accuracy Score: ' + str(accuraccyDict['avgAccuracy']) + '\nF1 Score: ' + str(accuraccyDict['avgF1']))
    ax.set_title(accuraccyDict['classifier'], fontsize=15)
    ax.set_xlabel('Classifer Accuracy (By K-Fold)', fontsize=15)
    ax.set_ylabel('Frequency', fontsize=15)
    ax.xaxis.set_ticks(np.arange(0, 1.1, 0.1))
    ax.yaxis.set_ticks(np.arange(0, .5, 1))
    ax.xaxis.set_tick_params(labelsize=15)
    ax.yaxis.set_tick_params(labelsize=15)
    plt.subplots_adjust(left=0.125, right=0.9, bottom=0.1,
                        top=0.6, wspace=0.2, hspace=0.2)
    plt.show()

modelDictionary = {
    'RandomForestClassifier': RandomForestClassifier,
    'KNeighborsClassifier': KNeighborsClassifier,
    'LogisticRegression': LogisticRegression,
    'GaussianNB': GaussianNB,
    'AdaBoostClassifier': AdaBoostClassifier,
    'DecisionTreeClassifier': DecisionTreeClassifier,
    'SVC': SVC,
    'MLPClassifier': MLPClassifier
}

modelParamsDictionary = {
    'RandomForestClassifier': {   # https://sklearn.org/modules/generated/sklearn.ensemble.RandomForestClassifier.html
        'n_estimators': [200, 500, 700],
        'criterion': ['gini', 'entropy'],
        'max_features': ["auto", "sqrt", "log2"],
        'bootstrap': [True],
        'oob_score': [True, False],
        'n_jobs': [-1]
    },
    'KNeighborsClassifier': {  # https://sklearn.org/modules/generated/sklearn.neighbors.KNeighborsClassifier.html
        'n_neighbors': np.arange(12, 18),
        'weights': ['uniform', 'distance'],
        'algorithm': ['auto', 'ball_tree', 'kd_tree', 'brute'],
        'n_jobs': [-1]
    },
    'LogisticRegression': {  # https://sklearn.org/modules/generated/sklearn.linear_model.LogisticRegression.html
        'C': [0.0001, 0.001, 1],
        'solver': ['newton-cg', 'lbfgs'],
        'multi_class': ['ovr', 'multinomial'],
        'max_iter': [100, 1000],
        'n_jobs': [-1]
    },
    'GaussianNB': {  # https://sklearn.org/modules/naive_bayes.html#gaussian-naive-bayes
        'var_smoothing': [1e-9]
    },
    'AdaBoostClassifier': {   # https://sklearn.org/modules/generated/sklearn.ensemble.AdaBoostClassifier.html
        'n_estimators': [20, 50, 100, 300],
        'learning_rate': [1]
    },
    'DecisionTreeClassifier': {   # https://sklearn.org/modules/generated/sklearn.tree.DecisionTreeClassifier.html
        'criterion': ['gini', 'entropy'],
        'splitter': ['best', 'random'],
        'max_features': ["auto", "sqrt", "log2"]
    },
    'SVC': {    # https://sklearn.org/modules/generated/sklearn.svm.SVC.html
        'C': [0.0001, 0.001, 1.0],
        'kernel': ['linear'],
        'gamma': ['scale', 'auto'], 
        'cache_size': [4000]
    },
    'MLPClassifier': {    # https://sklearn.org/modules/generated/sklearn.neural_network.MLPClassifier.html
        'activation': ['identity', 'logistic'],
        'solver': ['adam'],
        'learning_rate': ['constant', 'invscaling', 'adaptive'],
        'max_iter': [5000, 7000, 9000]
    }
}

now = datetime.datetime.now()
print ("Current date and time : ")
print (now.strftime("%Y-%m-%d %H:%M:%S"))

Current date and time : 
2021-06-05 09:02:04

n_folds = 5
l = len(df_features['Features']) - 1
df = df_features['Features']

# SMOTE Dataset
X = pd.concat([X_sm, X_test_ord]) #.to_numpy()
y = pd.concat([y_sm, y_test_ord]).to_numpy()
#data = (X, y, n_folds)

print('********************************************')
print('Starting SMOTE data set....')
print('********************************************')

for i in range(l ,6 , -1):
    col = []
    col = df[:i]
    nX = X.loc[:, col]
    nX = nX.to_numpy()
    data = (nX, y, n_folds)
    hyper_search(modelDictionary, modelParamsDictionary, data, col)

********************************************
Starting SMOTE data set....
********************************************

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgAccuracy': 0.778552920071756, 'f1': [0.7513006208760027, 0.809542780416137, 0.7881332879972798, 0.9085173501577286, 0.7188681233776127], 'avgF1': 0.7952724325649522, 'precision': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgPrecision': 0.778552920071756, 'recall': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgRecall': 0.778552920071756, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7528735632183908, 0.7011494252873564, 0.8092485549132948, 0.7803468208092486, 0.6878612716763006], 'avgAccuracy': 0.7462959271809182, 'f1': [0.7614140312830404, 0.7269124058660326, 0.8098284444609322, 0.8766233766233766, 0.6945299026787184], 'avgF1': 0.77386163218242, 'precision': [0.7528735632183908, 0.7011494252873564, 0.8092485549132948, 0.7803468208092486, 0.6878612716763006], 'avgPrecision': 0.7462959271809182, 'recall': [0.7528735632183908, 0.7011494252873564, 0.8092485549132948, 0.7803468208092486, 0.6878612716763006], 'avgRecall': 0.7462959271809182, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.6609195402298851, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6647398843930635], 'avgAccuracy': 0.648169556840077, 'f1': [0.6727523667809623, 0.7007398731536663, 0.7575712193301322, 0.6536964980544747, 0.6754816535722745], 'avgF1': 0.692048322178302, 'precision': [0.6609195402298851, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6647398843930635], 'avgPrecision': 0.648169556840077, 'recall': [0.6609195402298851, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6647398843930635], 'avgRecall': 0.648169556840077, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgAccuracy': 0.5866985582353332, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6083727447889298], 'avgF1': 0.5370210108736294, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgPrecision': 0.5866985582353332, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgRecall': 0.5866985582353332, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7413793103448276, 0.7758620689655172, 0.791907514450867, 0.630057803468208, 0.6647398843930635], 'avgAccuracy': 0.7207893163244967, 'f1': [0.7487416194991541, 0.7853084951776985, 0.7915524562923408, 0.7730496453900708, 0.6761087339122022], 'avgF1': 0.7549521900542933, 'precision': [0.7413793103448276, 0.7758620689655172, 0.791907514450867, 0.630057803468208, 0.6647398843930635], 'avgPrecision': 0.7207893163244967, 'recall': [0.7413793103448276, 0.7758620689655172, 0.791907514450867, 0.630057803468208, 0.6647398843930635], 'avgRecall': 0.7207893163244967, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7298850574712644, 0.764367816091954, 0.7456647398843931, 0.815028901734104, 0.7052023121387283], 'avgAccuracy': 0.7520297654640887, 'f1': [0.7370073707540847, 0.7780496848350018, 0.7441433449703351, 0.8980891719745221, 0.7109950617364541], 'avgF1': 0.7736569268540796, 'precision': [0.7298850574712644, 0.764367816091954, 0.7456647398843931, 0.815028901734104, 0.7052023121387283], 'avgPrecision': 0.7520297654640887, 'recall': [0.7298850574712644, 0.764367816091954, 0.7456647398843931, 0.815028901734104, 0.7052023121387283], 'avgRecall': 0.7520297654640887, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.632183908045977, 0.6954022988505747, 0.7052023121387283, 0.1791907514450867, 0.6647398843930635], 'avgAccuracy': 0.575343830974686, 'f1': [0.6435917379656038, 0.7209330675066161, 0.706315018674652, 0.30392156862745096, 0.6777699519114003], 'avgF1': 0.6105062689371447, 'precision': [0.632183908045977, 0.6954022988505747, 0.7052023121387283, 0.1791907514450867, 0.6647398843930635], 'avgPrecision': 0.575343830974686, 'recall': [0.632183908045977, 0.6954022988505747, 0.7052023121387283, 0.1791907514450867, 0.6647398843930635], 'avgRecall': 0.575343830974686, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.6839080459770115, 0.6896551724137931, 0.7572254335260116, 0.49710982658959535, 0.6820809248554913], 'avgAccuracy': 0.6619958806723806, 'f1': [0.69462582219584, 0.7154500671742051, 0.7572254335260116, 0.664092664092664, 0.6925765699788141], 'avgF1': 0.704794111393507, 'precision': [0.6839080459770115, 0.6896551724137931, 0.7572254335260116, 0.49710982658959535, 0.6820809248554913], 'avgPrecision': 0.6619958806723806, 'recall': [0.6839080459770115, 0.6896551724137931, 0.7572254335260116, 0.49710982658959535, 0.6820809248554913], 'avgRecall': 0.6619958806723806, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgAccuracy': 0.778552920071756, 'f1': [0.7513006208760027, 0.809542780416137, 0.7881332879972798, 0.9085173501577286, 0.7188681233776127], 'avgF1': 0.7952724325649522, 'precision': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgPrecision': 0.778552920071756, 'recall': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgRecall': 0.778552920071756, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.778553  0.795272   0.778553  0.778553   
1  0.746296  0.773862   0.746296  0.746296   
2  0.648170  0.692048   0.648170  0.648170   
3  0.586699  0.537021   0.586699  0.586699   
4  0.720789  0.754952   0.720789  0.720789   
5  0.752030  0.773657   0.752030  0.752030   
6  0.575344  0.610506   0.575344  0.575344   
7  0.661996  0.704794   0.661996  0.661996   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgAccuracy': 0.7739352866919141, 'f1': [0.7460770183694619, 0.809542780416137, 0.7999036608863198, 0.8980891719745221, 0.7059631398632363], 'avgF1': 0.7919151543019355, 'precision': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgPrecision': 0.7739352866919141, 'recall': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgRecall': 0.7739352866919141, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7298850574712644, 0.7126436781609196, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgAccuracy': 0.7463092153345293, 'f1': [0.7392199876814629, 0.7372040475488753, 0.8099685414953629, 0.8802588996763754, 0.6985286449786023], 'avgF1': 0.7730360242761357, 'precision': [0.7298850574712644, 0.7126436781609196, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgPrecision': 0.7463092153345293, 'recall': [0.7298850574712644, 0.7126436781609196, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgRecall': 0.7463092153345293, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.6551724137931034, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgAccuracy': 0.6493189821274333, 'f1': [0.6671455938697318, 0.7110521992222772, 0.7631828519322299, 0.6484375, 0.6754816535722745], 'avgF1': 0.6930599597193027, 'precision': [0.6551724137931034, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgPrecision': 0.6493189821274333, 'recall': [0.6551724137931034, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgRecall': 0.6493189821274333, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgAccuracy': 0.5866985582353332, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6083727447889298], 'avgF1': 0.5370210108736294, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgPrecision': 0.5866985582353332, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgRecall': 0.5866985582353332, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7068965517241379, 0.764367816091954, 0.8208092485549133, 0.630057803468208, 0.6589595375722543], 'avgAccuracy': 0.7162181914822935, 'f1': [0.7162071512876903, 0.7769116254290009, 0.8209431319487592, 0.7730496453900708, 0.6702185023409096], 'avgF1': 0.7514660112792861, 'precision': [0.7068965517241379, 0.764367816091954, 0.8208092485549133, 0.630057803468208, 0.6589595375722543], 'avgPrecision': 0.7162181914822935, 'recall': [0.7068965517241379, 0.764367816091954, 0.8208092485549133, 0.630057803468208, 0.6589595375722543], 'avgRecall': 0.7162181914822935, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7528735632183908, 0.7528735632183908, 0.7456647398843931, 0.7861271676300579, 0.653179190751445], 'avgAccuracy': 0.7381436449405355, 'f1': [0.7555943058513662, 0.7692864045654093, 0.7441433449703351, 0.8802588996763754, 0.6626681671696762], 'avgF1': 0.7623902244466324, 'precision': [0.7528735632183908, 0.7528735632183908, 0.7456647398843931, 0.7861271676300579, 0.653179190751445], 'avgPrecision': 0.7381436449405355, 'recall': [0.7528735632183908, 0.7528735632183908, 0.7456647398843931, 0.7861271676300579, 0.653179190751445], 'avgRecall': 0.7381436449405355, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.6264367816091954, 0.6551724137931034, 0.7341040462427746, 0.12716763005780346, 0.653179190751445], 'avgAccuracy': 0.5592120124908644, 'f1': [0.6363903285293359, 0.6850557771961477, 0.7352264963289916, 0.22564102564102562, 0.6665109396848238], 'avgF1': 0.589764913476065, 'precision': [0.6264367816091954, 0.6551724137931034, 0.7341040462427746, 0.12716763005780346, 0.653179190751445], 'avgPrecision': 0.5592120124908644, 'recall': [0.6264367816091954, 0.6551724137931034, 0.7341040462427746, 0.12716763005780346, 0.653179190751445], 'avgRecall': 0.5592120124908644, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.6781609195402298, 0.6666666666666666, 0.7630057803468208, 0.47398843930635837, 0.6763005780346821], 'avgAccuracy': 0.6516244767789515, 'f1': [0.6894341290893015, 0.6954022988505747, 0.763487329101577, 0.6431372549019608, 0.6866719413801271], 'avgF1': 0.6956265906647082, 'precision': [0.6781609195402298, 0.6666666666666666, 0.7630057803468208, 0.47398843930635837, 0.6763005780346821], 'avgPrecision': 0.6516244767789515, 'recall': [0.6781609195402298, 0.6666666666666666, 0.7630057803468208, 0.47398843930635837, 0.6763005780346821], 'avgRecall': 0.6516244767789515, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgAccuracy': 0.7739352866919141, 'f1': [0.7460770183694619, 0.809542780416137, 0.7999036608863198, 0.8980891719745221, 0.7059631398632363], 'avgF1': 0.7919151543019355, 'precision': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgPrecision': 0.7739352866919141, 'recall': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgRecall': 0.7739352866919141, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.773935  0.791915   0.773935  0.773935   
1  0.746309  0.773036   0.746309  0.746309   
2  0.649319  0.693060   0.649319  0.649319   
3  0.586699  0.537021   0.586699  0.586699   
4  0.716218  0.751466   0.716218  0.716218   
5  0.738144  0.762390   0.738144  0.738144   
6  0.559212  0.589765   0.559212  0.559212   
7  0.651624  0.695627   0.651624  0.651624   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgAccuracy': 0.7750847119792705, 'f1': [0.7460770183694619, 0.8158374552210141, 0.7943811144786455, 0.8980891719745221, 0.7124443868748527], 'avgF1': 0.7933658293836993, 'precision': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgPrecision': 0.7750847119792705, 'recall': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgRecall': 0.7750847119792705, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7298850574712644, 0.7068965517241379, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgAccuracy': 0.7451597900471729, 'f1': [0.7392199876814629, 0.7318084132477162, 0.8099685414953629, 0.8802588996763754, 0.6985286449786023], 'avgF1': 0.7719568974159039, 'precision': [0.7298850574712644, 0.7068965517241379, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgPrecision': 0.7451597900471729, 'recall': [0.7298850574712644, 0.7068965517241379, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgRecall': 0.7451597900471729, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6494252873563219, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgAccuracy': 0.648169556840077, 'f1': [0.6612784074000162, 0.7110521992222772, 0.7631828519322299, 0.6484375, 0.6754816535722745], 'avgF1': 0.6918865224253595, 'precision': [0.6494252873563219, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgPrecision': 0.648169556840077, 'recall': [0.6494252873563219, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgRecall': 0.648169556840077, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7413793103448276, 0.7816091954022989, 0.7976878612716763, 0.6127167630057804, 0.6416184971098265], 'avgAccuracy': 0.7150023254268819, 'f1': [0.7481985464666768, 0.7914596897355518, 0.7971484175626274, 0.7598566308243728, 0.6547897831134825], 'avgF1': 0.7502906135405423, 'precision': [0.7413793103448276, 0.7816091954022989, 0.7976878612716763, 0.6127167630057804, 0.6416184971098265], 'avgPrecision': 0.7150023254268819, 'recall': [0.7413793103448276, 0.7816091954022989, 0.7976878612716763, 0.6127167630057804, 0.6416184971098265], 'avgRecall': 0.7150023254268819, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6896551724137931, 0.7471264367816092, 0.7745664739884393, 0.861271676300578, 0.6647398843930635], 'avgAccuracy': 0.7474719287754966, 'f1': [0.697476362625139, 0.7612131434282859, 0.7739653795697847, 0.9254658385093167, 0.6719024880623272], 'avgF1': 0.7660046424389707, 'precision': [0.6896551724137931, 0.7471264367816092, 0.7745664739884393, 0.861271676300578, 0.6647398843930635], 'avgPrecision': 0.7474719287754966, 'recall': [0.6896551724137931, 0.7471264367816092, 0.7745664739884393, 0.861271676300578, 0.6647398843930635], 'avgRecall': 0.7474719287754966, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6264367816091954, 0.6551724137931034, 0.7283236994219653, 0.12716763005780346, 0.653179190751445], 'avgAccuracy': 0.5580559431267025, 'f1': [0.6355735479569788, 0.6850557771961477, 0.7295077122643383, 0.22564102564102562, 0.6665109396848238], 'avgF1': 0.5884578005486628, 'precision': [0.6264367816091954, 0.6551724137931034, 0.7283236994219653, 0.12716763005780346, 0.653179190751445], 'avgPrecision': 0.5580559431267025, 'recall': [0.6264367816091954, 0.6551724137931034, 0.7283236994219653, 0.12716763005780346, 0.653179190751445], 'avgRecall': 0.5580559431267025, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6781609195402298, 0.6781609195402298, 0.7745664739884393, 0.4797687861271676, 0.6705202312138728], 'avgAccuracy': 0.6562354660819879, 'f1': [0.6894341290893015, 0.7059056678557273, 0.7752517979992833, 0.6484375, 0.680730512429674], 'avgF1': 0.6999519214747972, 'precision': [0.6781609195402298, 0.6781609195402298, 0.7745664739884393, 0.4797687861271676, 0.6705202312138728], 'avgPrecision': 0.6562354660819879, 'recall': [0.6781609195402298, 0.6781609195402298, 0.7745664739884393, 0.4797687861271676, 0.6705202312138728], 'avgRecall': 0.6562354660819879, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgAccuracy': 0.7750847119792705, 'f1': [0.7460770183694619, 0.8158374552210141, 0.7943811144786455, 0.8980891719745221, 0.7124443868748527], 'avgF1': 0.7933658293836993, 'precision': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgPrecision': 0.7750847119792705, 'recall': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgRecall': 0.7750847119792705, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.775085  0.793366   0.775085  0.775085   
1  0.745160  0.771957   0.745160  0.745160   
2  0.648170  0.691887   0.648170  0.648170   
3  0.589011  0.538441   0.589011  0.589011   
4  0.715002  0.750291   0.715002  0.715002   
5  0.747472  0.766005   0.747472  0.747472   
6  0.558056  0.588458   0.558056  0.558056   
7  0.656235  0.699952   0.656235  0.656235   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgAccuracy': 0.7796890572055013, 'f1': [0.756521894452929, 0.8207461462740112, 0.7888626829315445, 0.9050632911392403, 0.7093979325981428], 'avgF1': 0.7961183894791736, 'precision': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgPrecision': 0.7796890572055013, 'recall': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgRecall': 0.7796890572055013, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7241379310344828, 0.7068965517241379, 0.8034682080924855, 0.7861271676300579, 0.6878612716763006], 'avgAccuracy': 0.7416982260314929, 'f1': [0.7335910291247274, 0.7318084132477162, 0.8039733628606461, 0.8802588996763754, 0.6922203519024327], 'avgF1': 0.7683704113623796, 'precision': [0.7241379310344828, 0.7068965517241379, 0.8034682080924855, 0.7861271676300579, 0.6878612716763006], 'avgPrecision': 0.7416982260314929, 'recall': [0.7241379310344828, 0.7068965517241379, 0.8034682080924855, 0.7861271676300579, 0.6878612716763006], 'avgRecall': 0.7416982260314929, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.6436781609195402, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6878612716763006], 'avgAccuracy': 0.6493455584346555, 'f1': [0.6555716060888476, 0.7005450064667237, 0.7575712193301322, 0.6536964980544747, 0.6964013504527086], 'avgF1': 0.6927571360785774, 'precision': [0.6436781609195402, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6878612716763006], 'avgPrecision': 0.6493455584346555, 'recall': [0.6436781609195402, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6878612716763006], 'avgRecall': 0.6493455584346555, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7528735632183908, 0.7988505747126436, 0.7976878612716763, 0.6184971098265896, 0.6242774566473989], 'avgAccuracy': 0.7184373131353399, 'f1': [0.759908658632525, 0.8060579417292026, 0.7971484175626274, 0.7642857142857142, 0.6386013066534284], 'avgF1': 0.7532004077726996, 'precision': [0.7528735632183908, 0.7988505747126436, 0.7976878612716763, 0.6184971098265896, 0.6242774566473989], 'avgPrecision': 0.7184373131353399, 'recall': [0.7528735632183908, 0.7988505747126436, 0.7976878612716763, 0.6184971098265896, 0.6242774566473989], 'avgRecall': 0.7184373131353399, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7471264367816092, 0.7241379310344828, 0.7687861271676301, 0.7861271676300579, 0.6820809248554913], 'avgAccuracy': 0.7416517174938543, 'f1': [0.7534992584352984, 0.7429641097818438, 0.7654029810350493, 0.8802588996763754, 0.6844438119544635], 'avgF1': 0.7653138121766061, 'precision': [0.7471264367816092, 0.7241379310344828, 0.7687861271676301, 0.7861271676300579, 0.6820809248554913], 'avgPrecision': 0.7416517174938543, 'recall': [0.7471264367816092, 0.7241379310344828, 0.7687861271676301, 0.7861271676300579, 0.6820809248554913], 'avgRecall': 0.7416517174938543, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.6264367816091954, 0.6494252873563219, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgAccuracy': 0.5545943791110225, 'f1': [0.6355735479569788, 0.6798662051724348, 0.7295077122643383, 0.18848167539267016, 0.6773916573765312], 'avgF1': 0.5821641596325906, 'precision': [0.6264367816091954, 0.6494252873563219, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgPrecision': 0.5545943791110225, 'recall': [0.6264367816091954, 0.6494252873563219, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgRecall': 0.5545943791110225, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.6781609195402298, 0.6666666666666666, 0.7687861271676301, 0.48554913294797686, 0.6994219653179191], 'avgAccuracy': 0.6597169623280845, 'f1': [0.6893358876117496, 0.6951566951566953, 0.7693804268948776, 0.6536964980544747, 0.7083970705689648], 'avgF1': 0.7031933156573524, 'precision': [0.6781609195402298, 0.6666666666666666, 0.7687861271676301, 0.48554913294797686, 0.6994219653179191], 'avgPrecision': 0.6597169623280845, 'recall': [0.6781609195402298, 0.6666666666666666, 0.7687861271676301, 0.48554913294797686, 0.6994219653179191], 'avgRecall': 0.6597169623280845, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgAccuracy': 0.7796890572055013, 'f1': [0.756521894452929, 0.8207461462740112, 0.7888626829315445, 0.9050632911392403, 0.7093979325981428], 'avgF1': 0.7961183894791736, 'precision': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgPrecision': 0.7796890572055013, 'recall': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgRecall': 0.7796890572055013, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.779689  0.796118   0.779689  0.779689   
1  0.741698  0.768370   0.741698  0.741698   
2  0.649346  0.692757   0.649346  0.649346   
3  0.589011  0.538441   0.589011  0.589011   
4  0.718437  0.753200   0.718437  0.718437   
5  0.741652  0.765314   0.741652  0.741652   
6  0.554594  0.582164   0.554594  0.554594   
7  0.659717  0.703193   0.659717  0.659717   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgAccuracy': 0.7762142050362102, 'f1': [0.7626051381089116, 0.8193172070681077, 0.782631463877425, 0.8980891719745221, 0.7044101270853962], 'avgF1': 0.7934106216228726, 'precision': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgPrecision': 0.7762142050362102, 'recall': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgRecall': 0.7762142050362102, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7413793103448276, 0.7126436781609196, 0.7976878612716763, 0.7861271676300579, 0.6878612716763006], 'avgAccuracy': 0.7451398578167564, 'f1': [0.7499080499966836, 0.7369089365728758, 0.7980989394769558, 0.8802588996763754, 0.6922203519024327], 'avgF1': 0.7714790355250647, 'precision': [0.7413793103448276, 0.7126436781609196, 0.7976878612716763, 0.7861271676300579, 0.6878612716763006], 'avgPrecision': 0.7451398578167564, 'recall': [0.7413793103448276, 0.7126436781609196, 0.7976878612716763, 0.7861271676300579, 0.6878612716763006], 'avgRecall': 0.7451398578167564, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.6551724137931034, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6936416184971098], 'avgAccuracy': 0.65280047837353, 'f1': [0.666958193221306, 0.7005450064667237, 0.7575712193301322, 0.6536964980544747, 0.7031353887503986], 'avgF1': 0.6963812611646071, 'precision': [0.6551724137931034, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6936416184971098], 'avgPrecision': 0.65280047837353, 'recall': [0.6551724137931034, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6936416184971098], 'avgRecall': 0.65280047837353, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7183908045977011, 0.7931034482758621, 0.791907514450867, 0.6473988439306358, 0.630057803468208], 'avgAccuracy': 0.7161716829446548, 'f1': [0.7258161950414926, 0.7983394145582627, 0.7911378573125346, 0.7859649122807019, 0.6440183805534138], 'avgF1': 0.7490553519492811, 'precision': [0.7183908045977011, 0.7931034482758621, 0.791907514450867, 0.6473988439306358, 0.630057803468208], 'avgPrecision': 0.7161716829446548, 'recall': [0.7183908045977011, 0.7931034482758621, 0.791907514450867, 0.6473988439306358, 0.630057803468208], 'avgRecall': 0.7161716829446548, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7298850574712644, 0.7816091954022989, 0.7456647398843931, 0.8208092485549133, 0.6589595375722543], 'avgAccuracy': 0.7473855557770248, 'f1': [0.7356183742329876, 0.7886998059411853, 0.7441433449703351, 0.9015873015873017, 0.6643998123346705], 'avgF1': 0.766889727813296, 'precision': [0.7298850574712644, 0.7816091954022989, 0.7456647398843931, 0.8208092485549133, 0.6589595375722543], 'avgPrecision': 0.7473855557770248, 'recall': [0.7298850574712644, 0.7816091954022989, 0.7456647398843931, 0.8208092485549133, 0.6589595375722543], 'avgRecall': 0.7473855557770248, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.6264367816091954, 0.6494252873563219, 0.7341040462427746, 0.10404624277456648, 0.6647398843930635], 'avgAccuracy': 0.5557504484751844, 'f1': [0.6355735479569788, 0.6798662051724348, 0.7352264963289916, 0.18848167539267016, 0.6773916573765312], 'avgF1': 0.5833079164455213, 'precision': [0.6264367816091954, 0.6494252873563219, 0.7341040462427746, 0.10404624277456648, 0.6647398843930635], 'avgPrecision': 0.5557504484751844, 'recall': [0.6264367816091954, 0.6494252873563219, 0.7341040462427746, 0.10404624277456648, 0.6647398843930635], 'avgRecall': 0.5557504484751844, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.6724137931034483, 0.6781609195402298, 0.7687861271676301, 0.48554913294797686, 0.6936416184971098], 'avgAccuracy': 0.659710318251279, 'f1': [0.6837098692033294, 0.7053380089616209, 0.7693804268948776, 0.6536964980544747, 0.7016031031087794], 'avgF1': 0.7027455812446164, 'precision': [0.6724137931034483, 0.6781609195402298, 0.7687861271676301, 0.48554913294797686, 0.6936416184971098], 'avgPrecision': 0.659710318251279, 'recall': [0.6724137931034483, 0.6781609195402298, 0.7687861271676301, 0.48554913294797686, 0.6936416184971098], 'avgRecall': 0.659710318251279, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgAccuracy': 0.7762142050362102, 'f1': [0.7626051381089116, 0.8193172070681077, 0.782631463877425, 0.8980891719745221, 0.7044101270853962], 'avgF1': 0.7934106216228726, 'precision': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgPrecision': 0.7762142050362102, 'recall': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgRecall': 0.7762142050362102, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.776214  0.793411   0.776214  0.776214   
1  0.745140  0.771479   0.745140  0.745140   
2  0.652800  0.696381   0.652800  0.652800   
3  0.589011  0.538441   0.589011  0.589011   
4  0.716172  0.749055   0.716172  0.716172   
5  0.747386  0.766890   0.747386  0.747386   
6  0.555750  0.583308   0.555750  0.555750   
7  0.659710  0.702746   0.659710  0.659710   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgAccuracy': 0.7808251943392466, 'f1': [0.7573624842197081, 0.8381601879214974, 0.7763629151082398, 0.9050632911392403, 0.707684646871162], 'avgF1': 0.7969267050519695, 'precision': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgPrecision': 0.7808251943392466, 'recall': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgRecall': 0.7808251943392466, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.735632183908046, 0.7241379310344828, 0.7745664739884393, 0.7630057803468208, 0.6820809248554913], 'avgAccuracy': 0.735884658826656, 'f1': [0.7441996594295445, 0.7470667263770712, 0.7747349079355358, 0.8655737704918033, 0.687152367430625], 'avgF1': 0.763745486332916, 'precision': [0.735632183908046, 0.7241379310344828, 0.7745664739884393, 0.7630057803468208, 0.6820809248554913], 'avgPrecision': 0.735884658826656, 'recall': [0.735632183908046, 0.7241379310344828, 0.7745664739884393, 0.7630057803468208, 0.6820809248554913], 'avgRecall': 0.735884658826656, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.6609195402298851, 0.6954022988505747, 0.7341040462427746, 0.4508670520231214, 0.7109826589595376], 'avgAccuracy': 0.6504551192611787, 'f1': [0.6726119698771305, 0.7212910961201756, 0.73448276402824, 0.6215139442231076, 0.7188901393080636], 'avgF1': 0.6937579827113435, 'precision': [0.6609195402298851, 0.6954022988505747, 0.7341040462427746, 0.4508670520231214, 0.7109826589595376], 'avgPrecision': 0.6504551192611787, 'recall': [0.6609195402298851, 0.6954022988505747, 0.7341040462427746, 0.4508670520231214, 0.7109826589595376], 'avgRecall': 0.6504551192611787, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7471264367816092, 0.7758620689655172, 0.7630057803468208, 0.6416184971098265, 0.5780346820809249], 'avgAccuracy': 0.7011294930569397, 'f1': [0.7540693402762367, 0.7877939851641717, 0.7612913297585413, 0.7816901408450704, 0.5944891736773938], 'avgF1': 0.7358667939442828, 'precision': [0.7471264367816092, 0.7758620689655172, 0.7630057803468208, 0.6416184971098265, 0.5780346820809249], 'avgPrecision': 0.7011294930569397, 'recall': [0.7471264367816092, 0.7758620689655172, 0.7630057803468208, 0.6416184971098265, 0.5780346820809249], 'avgRecall': 0.7011294930569397, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7471264367816092, 0.735632183908046, 0.7456647398843931, 0.8323699421965318, 0.6589595375722543], 'avgAccuracy': 0.7439505680685669, 'f1': [0.7545617816091953, 0.7526797117314359, 0.7434873322446296, 0.9085173501577286, 0.6678223223286411], 'avgF1': 0.7654136996143261, 'precision': [0.7471264367816092, 0.735632183908046, 0.7456647398843931, 0.8323699421965318, 0.6589595375722543], 'avgPrecision': 0.7439505680685669, 'recall': [0.7471264367816092, 0.735632183908046, 0.7456647398843931, 0.8323699421965318, 0.6589595375722543], 'avgRecall': 0.7439505680685669, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.6666666666666666, 0.6666666666666666, 0.7225433526011561, 0.10404624277456648, 0.653179190751445], 'avgAccuracy': 0.5626204238921002, 'f1': [0.6774410774410775, 0.6956140350877194, 0.7237720253553377, 0.18848167539267016, 0.6665109396848238], 'avgF1': 0.5903639505923257, 'precision': [0.6666666666666666, 0.6666666666666666, 0.7225433526011561, 0.10404624277456648, 0.653179190751445], 'avgPrecision': 0.5626204238921002, 'recall': [0.6666666666666666, 0.6666666666666666, 0.7225433526011561, 0.10404624277456648, 0.653179190751445], 'avgRecall': 0.5626204238921002, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.6666666666666666, 0.6954022988505747, 0.7572254335260116, 0.47398843930635837, 0.6994219653179191], 'avgAccuracy': 0.6585409607335061, 'f1': [0.6782407407407407, 0.7209330675066161, 0.7578494482396217, 0.6431372549019608, 0.707645744880386], 'avgF1': 0.701561251253865, 'precision': [0.6666666666666666, 0.6954022988505747, 0.7572254335260116, 0.47398843930635837, 0.6994219653179191], 'avgPrecision': 0.6585409607335061, 'recall': [0.6666666666666666, 0.6954022988505747, 0.7572254335260116, 0.47398843930635837, 0.6994219653179191], 'avgRecall': 0.6585409607335061, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgAccuracy': 0.7808251943392466, 'f1': [0.7573624842197081, 0.8381601879214974, 0.7763629151082398, 0.9050632911392403, 0.707684646871162], 'avgF1': 0.7969267050519695, 'precision': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgPrecision': 0.7808251943392466, 'recall': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgRecall': 0.7808251943392466, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.780825  0.796927   0.780825  0.780825   
1  0.735885  0.763745   0.735885  0.735885   
2  0.650455  0.693758   0.650455  0.650455   
3  0.589011  0.538441   0.589011  0.589011   
4  0.701129  0.735867   0.701129  0.701129   
5  0.743951  0.765414   0.743951  0.743951   
6  0.562620  0.590364   0.562620  0.562620   
7  0.658541  0.701561   0.658541  0.658541   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgAccuracy': 0.7819812637034084, 'f1': [0.7626051381089116, 0.8319495121318856, 0.7708818132762049, 0.9085173501577286, 0.7160018868075376], 'avgF1': 0.7979911400964537, 'precision': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgPrecision': 0.7819812637034084, 'recall': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgRecall': 0.7819812637034084, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7298850574712644, 0.7241379310344828, 0.7745664739884393, 0.7687861271676301, 0.6878612716763006], 'avgAccuracy': 0.7370473722676234, 'f1': [0.7387928522187587, 0.7470667263770712, 0.7747349079355358, 0.8692810457516339, 0.6922203519024327], 'avgF1': 0.7644191768370865, 'precision': [0.7298850574712644, 0.7241379310344828, 0.7745664739884393, 0.7687861271676301, 0.6878612716763006], 'avgPrecision': 0.7370473722676234, 'recall': [0.7298850574712644, 0.7241379310344828, 0.7745664739884393, 0.7687861271676301, 0.6878612716763006], 'avgRecall': 0.7370473722676234, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.6551724137931034, 0.6839080459770115, 0.7456647398843931, 0.4508670520231214, 0.7167630057803468], 'avgAccuracy': 0.6504750514915952, 'f1': [0.666958193221306, 0.710773778992635, 0.7460269916791861, 0.6215139442231076, 0.7248777846781], 'avgF1': 0.694030138558867, 'precision': [0.6551724137931034, 0.6839080459770115, 0.7456647398843931, 0.4508670520231214, 0.7167630057803468], 'avgPrecision': 0.6504750514915952, 'recall': [0.6551724137931034, 0.6839080459770115, 0.7456647398843931, 0.4508670520231214, 0.7167630057803468], 'avgRecall': 0.6504750514915952, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7471264367816092, 0.7873563218390804, 0.7687861271676301, 0.6242774566473989, 0.5664739884393064], 'avgAccuracy': 0.698804066175005, 'f1': [0.7545617816091953, 0.7975498607036771, 0.767403040882123, 0.7686832740213524, 0.5827172687489401], 'avgF1': 0.7341830451930575, 'precision': [0.7471264367816092, 0.7873563218390804, 0.7687861271676301, 0.6242774566473989, 0.5664739884393064], 'avgPrecision': 0.698804066175005, 'recall': [0.7471264367816092, 0.7873563218390804, 0.7687861271676301, 0.6242774566473989, 0.5664739884393064], 'avgRecall': 0.698804066175005, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7126436781609196, 0.7528735632183908, 0.7341040462427746, 0.8323699421965318, 0.6589595375722543], 'avgAccuracy': 0.7381901534781742, 'f1': [0.7205333412229964, 0.7701666995393626, 0.7331205954549055, 0.9085173501577286, 0.6656609537735448], 'avgF1': 0.7595997880297076, 'precision': [0.7126436781609196, 0.7528735632183908, 0.7341040462427746, 0.8323699421965318, 0.6589595375722543], 'avgPrecision': 0.7381901534781742, 'recall': [0.7126436781609196, 0.7528735632183908, 0.7341040462427746, 0.8323699421965318, 0.6589595375722543], 'avgRecall': 0.7381901534781742, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.6666666666666666, 0.6666666666666666, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgAccuracy': 0.5660886319845857, 'f1': [0.6774410774410775, 0.6956140350877194, 0.7295077122643383, 0.18848167539267016, 0.6776272416953296], 'avgF1': 0.593734348376227, 'precision': [0.6666666666666666, 0.6666666666666666, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgPrecision': 0.5660886319845857, 'recall': [0.6666666666666666, 0.6666666666666666, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgRecall': 0.5660886319845857, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.6666666666666666, 0.6839080459770115, 0.7630057803468208, 0.45664739884393063, 0.7109826589595376], 'avgAccuracy': 0.6562421101587934, 'f1': [0.6782407407407407, 0.7104022398653563, 0.763487329101577, 0.626984126984127, 0.7188901393080636], 'avgF1': 0.6996009151999729, 'precision': [0.6666666666666666, 0.6839080459770115, 0.7630057803468208, 0.45664739884393063, 0.7109826589595376], 'avgPrecision': 0.6562421101587934, 'recall': [0.6666666666666666, 0.6839080459770115, 0.7630057803468208, 0.45664739884393063, 0.7109826589595376], 'avgRecall': 0.6562421101587934, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgAccuracy': 0.7819812637034084, 'f1': [0.7626051381089116, 0.8319495121318856, 0.7708818132762049, 0.9085173501577286, 0.7160018868075376], 'avgF1': 0.7979911400964537, 'precision': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgPrecision': 0.7819812637034084, 'recall': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgRecall': 0.7819812637034084, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.781981  0.797991   0.781981  0.781981   
1  0.737047  0.764419   0.737047  0.737047   
2  0.650475  0.694030   0.650475  0.650475   
3  0.589011  0.538441   0.589011  0.589011   
4  0.698804  0.734183   0.698804  0.698804   
5  0.738190  0.759600   0.738190  0.738190   
6  0.566089  0.593734   0.566089  0.566089   
7  0.656242  0.699601   0.656242  0.656242   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgAccuracy': 0.732423094810976, 'f1': [0.7157671562434775, 0.767236450385442, 0.764010094465016, 0.8543046357615894, 0.7100861086068835], 'avgF1': 0.7622808890924817, 'precision': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgPrecision': 0.732423094810976, 'recall': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgRecall': 0.732423094810976, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6494252873563219, 0.6609195402298851, 0.7398843930635838, 0.7341040462427746, 0.6763005780346821], 'avgAccuracy': 0.6921267689854494, 'f1': [0.6612784074000162, 0.690126075975465, 0.7410180223807494, 0.8466666666666667, 0.688516082984237], 'avgF1': 0.7255210510814268, 'precision': [0.6494252873563219, 0.6609195402298851, 0.7398843930635838, 0.7341040462427746, 0.6763005780346821], 'avgPrecision': 0.6921267689854494, 'recall': [0.6494252873563219, 0.6609195402298851, 0.7398843930635838, 0.7341040462427746, 0.6763005780346821], 'avgRecall': 0.6921267689854494, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 16, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgAccuracy': 0.6366553717360972, 'f1': [0.6440729130384304, 0.6903623951667812, 0.7176240538965356, 0.6589147286821705, 0.6925765699788141], 'avgF1': 0.6807101321525464, 'precision': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgPrecision': 0.6366553717360972, 'recall': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgRecall': 0.6366553717360972, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6127167630057804], 'avgAccuracy': 0.6931632449671118, 'f1': [0.7060784028789387, 0.7397835063050998, 0.7698100211294482, 0.8027681660899654, 0.6275255539756237], 'avgF1': 0.7291931300758152, 'precision': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6127167630057804], 'avgPrecision': 0.6931632449671118, 'recall': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6127167630057804], 'avgRecall': 0.6931632449671118, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6781609195402298, 0.6494252873563219, 0.7052023121387283, 0.7514450867052023, 0.6589595375722543], 'avgAccuracy': 0.6886386286625473, 'f1': [0.6894272677690964, 0.6796218751610743, 0.7059513050273538, 0.858085808580858, 0.6719611860392657], 'avgF1': 0.7210094885155296, 'precision': [0.6781609195402298, 0.6494252873563219, 0.7052023121387283, 0.7514450867052023, 0.6589595375722543], 'avgPrecision': 0.6886386286625473, 'recall': [0.6781609195402298, 0.6494252873563219, 0.7052023121387283, 0.7514450867052023, 0.6589595375722543], 'avgRecall': 0.6886386286625473, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6494252873563219, 0.6724137931034483, 0.7109826589595376, 0.10404624277456648, 0.6647398843930635], 'avgAccuracy': 0.5603215733173875, 'f1': [0.6605387426298953, 0.7008436261117909, 0.7119772530481384, 0.18848167539267016, 0.6766345057538314], 'avgF1': 0.5876951605872652, 'precision': [0.6494252873563219, 0.6724137931034483, 0.7109826589595376, 0.10404624277456648, 0.6647398843930635], 'avgPrecision': 0.5603215733173875, 'recall': [0.6494252873563219, 0.6724137931034483, 0.7109826589595376, 0.10404624277456648, 0.6647398843930635], 'avgRecall': 0.5603215733173875, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6264367816091954, 0.6724137931034483, 0.7225433526011561, 0.49710982658959535, 0.6878612716763006], 'avgAccuracy': 0.6412730051159391, 'f1': [0.6387204866421128, 0.7008436261117909, 0.7234981629262128, 0.664092664092664, 0.6971815732831559], 'avgF1': 0.6848673026111872, 'precision': [0.6264367816091954, 0.6724137931034483, 0.7225433526011561, 0.49710982658959535, 0.6878612716763006], 'avgPrecision': 0.6412730051159391, 'recall': [0.6264367816091954, 0.6724137931034483, 0.7225433526011561, 0.49710982658959535, 0.6878612716763006], 'avgRecall': 0.6412730051159391, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgAccuracy': 0.732423094810976, 'f1': [0.7157671562434775, 0.767236450385442, 0.764010094465016, 0.8543046357615894, 0.7100861086068835], 'avgF1': 0.7622808890924817, 'precision': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgPrecision': 0.732423094810976, 'recall': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgRecall': 0.732423094810976, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.732423  0.762281   0.732423  0.732423   
1  0.692127  0.725521   0.692127  0.692127   
2  0.636655  0.680710   0.636655  0.636655   
3  0.589011  0.538441   0.589011  0.589011   
4  0.693163  0.729193   0.693163  0.693163   
5  0.688639  0.721009   0.688639  0.688639   
6  0.560322  0.587695   0.560322  0.560322   
7  0.641273  0.684867   0.641273  0.641273   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgAccuracy': 0.7266626802205833, 'f1': [0.7099366509926854, 0.7571732652192422, 0.758206208774358, 0.8543046357615894, 0.7047170545733049], 'avgF1': 0.756867563064236, 'precision': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgPrecision': 0.7266626802205833, 'recall': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgRecall': 0.7266626802205833, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6494252873563219, 0.6724137931034483, 0.7456647398843931, 0.7109826589595376, 0.6878612716763006], 'avgAccuracy': 0.6932695501960003, 'f1': [0.6615140705509314, 0.7007868423511822, 0.7467383877929485, 0.8310810810810811, 0.6955185553773727], 'avgF1': 0.7271277874307032, 'precision': [0.6494252873563219, 0.6724137931034483, 0.7456647398843931, 0.7109826589595376, 0.6878612716763006], 'avgPrecision': 0.6932695501960003, 'recall': [0.6494252873563219, 0.6724137931034483, 0.7456647398843931, 0.7109826589595376, 0.6878612716763006], 'avgRecall': 0.6932695501960003, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 14, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgAccuracy': 0.6366553717360972, 'f1': [0.6440729130384304, 0.6903623951667812, 0.7176240538965356, 0.6589147286821705, 0.693122877416869], 'avgF1': 0.6808193936401573, 'precision': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgPrecision': 0.6366553717360972, 'recall': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgRecall': 0.6366553717360972, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6184971098265896], 'avgAccuracy': 0.6943193143312737, 'f1': [0.7060784028789387, 0.7397835063050998, 0.7698100211294482, 0.8027681660899654, 0.6321668489298549], 'avgF1': 0.7301213890666614, 'precision': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6184971098265896], 'avgPrecision': 0.6943193143312737, 'recall': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6184971098265896], 'avgRecall': 0.6943193143312737, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6609195402298851, 0.6839080459770115, 0.7572254335260116, 0.6878612716763006, 0.6878612716763006], 'avgAccuracy': 0.6955551126171019, 'f1': [0.67280425980863, 0.7112402284816078, 0.7574038965192762, 0.815068493150685, 0.6996405085919428], 'avgF1': 0.7312314773104284, 'precision': [0.6609195402298851, 0.6839080459770115, 0.7572254335260116, 0.6878612716763006, 0.6878612716763006], 'avgPrecision': 0.6955551126171019, 'recall': [0.6609195402298851, 0.6839080459770115, 0.7572254335260116, 0.6878612716763006, 0.6878612716763006], 'avgRecall': 0.6955551126171019, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6436781609195402, 0.6724137931034483, 0.7167630057803468, 0.10404624277456648, 0.6647398843930635], 'avgAccuracy': 0.560328217394193, 'f1': [0.6547294961541786, 0.7008585851611275, 0.7178320767658422, 0.18848167539267016, 0.6776272416953296], 'avgF1': 0.5879058150338297, 'precision': [0.6436781609195402, 0.6724137931034483, 0.7167630057803468, 0.10404624277456648, 0.6647398843930635], 'avgPrecision': 0.560328217394193, 'recall': [0.6436781609195402, 0.6724137931034483, 0.7167630057803468, 0.10404624277456648, 0.6647398843930635], 'avgRecall': 0.560328217394193, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6264367816091954, 0.6781609195402298, 0.7167630057803468, 0.48554913294797686, 0.6820809248554913], 'avgAccuracy': 0.637798152946648, 'f1': [0.6387204866421128, 0.7060520587164044, 0.7176240538965356, 0.6536964980544747, 0.693122877416869], 'avgF1': 0.6818431949452793, 'precision': [0.6264367816091954, 0.6781609195402298, 0.7167630057803468, 0.48554913294797686, 0.6820809248554913], 'avgPrecision': 0.637798152946648, 'recall': [0.6264367816091954, 0.6781609195402298, 0.7167630057803468, 0.48554913294797686, 0.6820809248554913], 'avgRecall': 0.637798152946648, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgAccuracy': 0.7266626802205833, 'f1': [0.7099366509926854, 0.7571732652192422, 0.758206208774358, 0.8543046357615894, 0.7047170545733049], 'avgF1': 0.756867563064236, 'precision': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgPrecision': 0.7266626802205833, 'recall': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgRecall': 0.7266626802205833, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.726663  0.756868   0.726663  0.726663   
1  0.693270  0.727128   0.693270  0.693270   
2  0.636655  0.680819   0.636655  0.636655   
3  0.589011  0.538441   0.589011  0.589011   
4  0.694319  0.730121   0.694319  0.694319   
5  0.695555  0.731231   0.695555  0.695555   
6  0.560328  0.587906   0.560328  0.560328   
7  0.637798  0.681843   0.637798  0.637798   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6839080459770115, 0.7413793103448276, 0.7572254335260116, 0.7456647398843931, 0.6820809248554913], 'avgAccuracy': 0.7220516909175471, 'f1': [0.6939488886435876, 0.7622097742380217, 0.758206208774358, 0.8543046357615894, 0.6939330473089527], 'avgF1': 0.7525205109453019, 'precision': [0.6839080459770115, 0.7413793103448276, 0.7572254335260116, 0.7456647398843931, 0.6820809248554913], 'avgPrecision': 0.7220516909175471, 'recall': [0.6839080459770115, 0.7413793103448276, 0.7572254335260116, 0.7456647398843931, 0.6820809248554913], 'avgRecall': 0.7220516909175471, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgAccuracy': 0.7175137864593715, 'f1': [0.6802616577889917, 0.7059695958472377, 0.7525283324971606, 0.9015873015873017, 0.6776272416953296], 'avgF1': 0.7435948258832042, 'precision': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgPrecision': 0.7175137864593715, 'recall': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgRecall': 0.7175137864593715, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.632183908045977, 0.6839080459770115, 0.7225433526011561, 0.2658959537572254, 0.6820809248554913], 'avgAccuracy': 0.5973224370473723, 'f1': [0.6440729130384304, 0.7112402284816078, 0.7237553608055194, 0.4200913242009132, 0.6939330473089527], 'avgF1': 0.6386185747670847, 'precision': [0.632183908045977, 0.6839080459770115, 0.7225433526011561, 0.2658959537572254, 0.6820809248554913], 'avgPrecision': 0.5973224370473723, 'recall': [0.632183908045977, 0.6839080459770115, 0.7225433526011561, 0.2658959537572254, 0.6820809248554913], 'avgRecall': 0.5973224370473723, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6954022988505747, 0.7126436781609196, 0.7687861271676301, 0.6936416184971098, 0.6184971098265896], 'avgAccuracy': 0.6977941665005647, 'f1': [0.7060784028789387, 0.7340820264186416, 0.7698100211294482, 0.8191126279863481, 0.6321668489298549], 'avgF1': 0.7322499854686463, 'precision': [0.6954022988505747, 0.7126436781609196, 0.7687861271676301, 0.6936416184971098, 0.6184971098265896], 'avgPrecision': 0.6977941665005647, 'recall': [0.6954022988505747, 0.7126436781609196, 0.7687861271676301, 0.6936416184971098, 0.6184971098265896], 'avgRecall': 0.6977941665005647, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6264367816091954, 0.7126436781609196, 0.7398843930635838, 0.7167630057803468, 0.6647398843930635], 'avgAccuracy': 0.6920935486014218, 'f1': [0.639530116738321, 0.7372040475488753, 0.7402494675996348, 0.8350168350168351, 0.6773916573765312], 'avgF1': 0.7258784248560395, 'precision': [0.6264367816091954, 0.7126436781609196, 0.7398843930635838, 0.7167630057803468, 0.6647398843930635], 'avgPrecision': 0.6920935486014218, 'recall': [0.6264367816091954, 0.7126436781609196, 0.7398843930635838, 0.7167630057803468, 0.6647398843930635], 'avgRecall': 0.6920935486014218, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.632183908045977, 0.6551724137931034, 0.7283236994219653, 0.10404624277456648, 0.653179190751445], 'avgAccuracy': 0.5545810909574115, 'f1': [0.6423519009725907, 0.6850878202274172, 0.7294153169029419, 0.18848167539267016, 0.6665109396848238], 'avgF1': 0.5823695306360888, 'precision': [0.632183908045977, 0.6551724137931034, 0.7283236994219653, 0.10404624277456648, 0.653179190751445], 'avgPrecision': 0.5545810909574115, 'recall': [0.632183908045977, 0.6551724137931034, 0.7283236994219653, 0.10404624277456648, 0.653179190751445], 'avgRecall': 0.5545810909574115, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6206896551724138, 0.6839080459770115, 0.7283236994219653, 0.5086705202312138, 0.6936416184971098], 'avgAccuracy': 0.6470467078599429, 'f1': [0.6329501915708813, 0.7112402284816078, 0.7295277038428584, 0.6743295019157087, 0.704282045510801], 'avgF1': 0.6904659342643714, 'precision': [0.6206896551724138, 0.6839080459770115, 0.7283236994219653, 0.5086705202312138, 0.6936416184971098], 'avgPrecision': 0.6470467078599429, 'recall': [0.6206896551724138, 0.6839080459770115, 0.7283236994219653, 0.5086705202312138, 0.6936416184971098], 'avgRecall': 0.6470467078599429, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgAccuracy': 0.7175137864593715, 'f1': [0.6802616577889917, 0.7059695958472377, 0.7525283324971606, 0.9015873015873017, 0.6776272416953296], 'avgF1': 0.7435948258832042, 'precision': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgPrecision': 0.7175137864593715, 'recall': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgRecall': 0.7175137864593715, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.722052  0.752521   0.722052  0.722052   
1  0.717514  0.743595   0.717514  0.717514   
2  0.597322  0.638619   0.597322  0.597322   
3  0.589011  0.538441   0.589011  0.589011   
4  0.697794  0.732250   0.697794  0.697794   
5  0.692094  0.725878   0.692094  0.692094   
6  0.554581  0.582370   0.554581  0.554581   
7  0.647047  0.690466   0.647047  0.647047   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6763005780346821], 'avgAccuracy': 0.6723672845658096, 'f1': [0.6885908897403151, 0.7466155810983398, 0.7465399826823617, 0.6992481203007519, 0.6887435437058355], 'avgF1': 0.7139476235055208, 'precision': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6763005780346821], 'avgPrecision': 0.6723672845658096, 'recall': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6763005780346821], 'avgRecall': 0.6723672845658096, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgAccuracy': 0.7302039731579297, 'f1': [0.7060445027907718, 0.7060819655455894, 0.7408661929482224, 0.9015873015873017, 0.6864138286685275], 'avgF1': 0.7481987583080826, 'precision': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgPrecision': 0.7302039731579297, 'recall': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgRecall': 0.7302039731579297, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6264367816091954, 0.6666666666666666, 0.7167630057803468, 0.26011560693641617, 0.6936416184971098], 'avgAccuracy': 0.5927247358979469, 'f1': [0.6377432198933213, 0.6955848928865033, 0.7178320767658422, 0.4128440366972477, 0.7047170545733049], 'avgF1': 0.6337442561632438, 'precision': [0.6264367816091954, 0.6666666666666666, 0.7167630057803468, 0.26011560693641617, 0.6936416184971098], 'avgPrecision': 0.5927247358979469, 'recall': [0.6264367816091954, 0.6666666666666666, 0.7167630057803468, 0.26011560693641617, 0.6936416184971098], 'avgRecall': 0.5927247358979469, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgAccuracy': 0.6469337585542488, 'f1': [0.7060784028789387, 0.729883030266172, 0.7813195200729757, 0.6536964980544747, 0.5772928193873451], 'avgF1': 0.6896540541319812, 'precision': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgPrecision': 0.6469337585542488, 'recall': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgRecall': 0.6469337585542488, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6666666666666666, 0.6896551724137931, 0.7398843930635838, 0.4913294797687861, 0.6820809248554913], 'avgAccuracy': 0.6539233273536642, 'f1': [0.6783424908424908, 0.7165501994765329, 0.7409295587368592, 0.6589147286821705, 0.694201105629824], 'avgF1': 0.6977876166735755, 'precision': [0.6666666666666666, 0.6896551724137931, 0.7398843930635838, 0.4913294797687861, 0.6820809248554913], 'avgPrecision': 0.6539233273536642, 'recall': [0.6666666666666666, 0.6896551724137931, 0.7398843930635838, 0.4913294797687861, 0.6820809248554913], 'avgRecall': 0.6539233273536642, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6091954022988506, 0.632183908045977, 0.7052023121387283, 0.10404624277456648, 0.630057803468208], 'avgAccuracy': 0.5361371337452661, 'f1': [0.6199988947833777, 0.6634273772204807, 0.7064515809198981, 0.18848167539267016, 0.644309926201206], 'avgF1': 0.5645338909035266, 'precision': [0.6091954022988506, 0.632183908045977, 0.7052023121387283, 0.10404624277456648, 0.630057803468208], 'avgPrecision': 0.5361371337452661, 'recall': [0.6091954022988506, 0.632183908045977, 0.7052023121387283, 0.10404624277456648, 0.630057803468208], 'avgRecall': 0.5361371337452661, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.632183908045977, 0.6896551724137931, 0.7109826589595376, 0.2543352601156069, 0.6936416184971098], 'avgAccuracy': 0.5961597236064049, 'f1': [0.643017960828128, 0.7158616514987058, 0.7119772530481384, 0.40552995391705066, 0.7047170545733049], 'avgF1': 0.6362207747730656, 'precision': [0.632183908045977, 0.6896551724137931, 0.7109826589595376, 0.2543352601156069, 0.6936416184971098], 'avgPrecision': 0.5961597236064049, 'recall': [0.632183908045977, 0.6896551724137931, 0.7109826589595376, 0.2543352601156069, 0.6936416184971098], 'avgRecall': 0.5961597236064049, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgAccuracy': 0.7302039731579297, 'f1': [0.7060445027907718, 0.7060819655455894, 0.7408661929482224, 0.9015873015873017, 0.6864138286685275], 'avgF1': 0.7481987583080826, 'precision': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgPrecision': 0.7302039731579297, 'recall': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgRecall': 0.7302039731579297, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.672367  0.713948   0.672367  0.672367   
1  0.730204  0.748199   0.730204  0.730204   
2  0.592725  0.633744   0.592725  0.592725   
3  0.589011  0.538441   0.589011  0.589011   
4  0.646934  0.689654   0.646934  0.646934   
5  0.653923  0.697788   0.653923  0.653923   
6  0.536137  0.564534   0.536137  0.536137   
7  0.596160  0.636221   0.596160  0.596160   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6839080459770115, 0.7241379310344828, 0.7398843930635838, 0.5375722543352601, 0.6763005780346821], 'avgAccuracy': 0.672360640489004, 'f1': [0.6943320611070581, 0.7466155810983398, 0.7408661929482224, 0.6992481203007519, 0.6887435437058355], 'avgF1': 0.7139610998320416, 'precision': [0.6839080459770115, 0.7241379310344828, 0.7398843930635838, 0.5375722543352601, 0.6763005780346821], 'avgPrecision': 0.672360640489004, 'recall': [0.6839080459770115, 0.7241379310344828, 0.7398843930635838, 0.5375722543352601, 0.6763005780346821], 'avgRecall': 0.672360640489004, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6954022988505747, 0.6781609195402298, 0.7456647398843931, 0.8265895953757225, 0.6763005780346821], 'avgAccuracy': 0.7244236263371204, 'f1': [0.7059289222790964, 0.7060819655455894, 0.746692218715994, 0.9050632911392403, 0.688516082984237], 'avgF1': 0.7504564961328315, 'precision': [0.6954022988505747, 0.6781609195402298, 0.7456647398843931, 0.8265895953757225, 0.6763005780346821], 'avgPrecision': 0.7244236263371204, 'recall': [0.6954022988505747, 0.6781609195402298, 0.7456647398843931, 0.8265895953757225, 0.6763005780346821], 'avgRecall': 0.7244236263371204, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6149425287356322, 0.6781609195402298, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgAccuracy': 0.5892565278054614, 'f1': [0.625947848405732, 0.7061101028433151, 0.7178320767658422, 0.40552995391705066, 0.6939330473089527], 'avgF1': 0.6298706058481786, 'precision': [0.6149425287356322, 0.6781609195402298, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgPrecision': 0.5892565278054614, 'recall': [0.6149425287356322, 0.6781609195402298, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgRecall': 0.5892565278054614, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgAccuracy': 0.6469337585542488, 'f1': [0.7060784028789387, 0.729883030266172, 0.7813195200729757, 0.6536964980544747, 0.5772928193873451], 'avgF1': 0.6896540541319812, 'precision': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgPrecision': 0.6469337585542488, 'recall': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgRecall': 0.6469337585542488, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgAccuracy': 0.6504617633379841, 'f1': [0.6837348786775187, 0.7053380089616209, 0.7523832510394124, 0.626984126984127, 0.7050627546795359], 'avgF1': 0.694700604068443, 'precision': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgPrecision': 0.6504617633379841, 'recall': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgRecall': 0.6504617633379841, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.603448275862069, 0.6781609195402298, 0.6936416184971098, 0.10404624277456648, 0.6184971098265896], 'avgAccuracy': 0.5395588333001129, 'f1': [0.6140143487465257, 0.7061101028433151, 0.6946869653981668, 0.18848167539267016, 0.6329503615101394], 'avgF1': 0.5672486907781634, 'precision': [0.603448275862069, 0.6781609195402298, 0.6936416184971098, 0.10404624277456648, 0.6184971098265896], 'avgPrecision': 0.5395588333001129, 'recall': [0.603448275862069, 0.6781609195402298, 0.6936416184971098, 0.10404624277456648, 0.6184971098265896], 'avgRecall': 0.5395588333001129, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6206896551724138, 0.6954022988505747, 0.7225433526011561, 0.24277456647398843, 0.6994219653179191], 'avgAccuracy': 0.5961663676832104, 'f1': [0.6318622721040069, 0.7215593919778308, 0.7232565122738532, 0.39069767441860465, 0.7100861086068835], 'avgF1': 0.6354923918762359, 'precision': [0.6206896551724138, 0.6954022988505747, 0.7225433526011561, 0.24277456647398843, 0.6994219653179191], 'avgPrecision': 0.5961663676832104, 'recall': [0.6206896551724138, 0.6954022988505747, 0.7225433526011561, 0.24277456647398843, 0.6994219653179191], 'avgRecall': 0.5961663676832104, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgAccuracy': 0.6504617633379841, 'f1': [0.6837348786775187, 0.7053380089616209, 0.7523832510394124, 0.626984126984127, 0.7050627546795359], 'avgF1': 0.694700604068443, 'precision': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgPrecision': 0.6504617633379841, 'recall': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgRecall': 0.6504617633379841, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.672361  0.713961   0.672361  0.672361   
1  0.724424  0.750456   0.724424  0.724424   
2  0.589257  0.629871   0.589257  0.589257   
3  0.589011  0.538441   0.589011  0.589011   
4  0.646934  0.689654   0.646934  0.646934   
5  0.650462  0.694701   0.650462  0.650462   
6  0.539559  0.567249   0.539559  0.539559   
7  0.596166  0.635492   0.596166  0.596166   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6705202312138728], 'avgAccuracy': 0.6712112152016477, 'f1': [0.6889352784899223, 0.7466155810983398, 0.746692218715994, 0.6992481203007519, 0.6832668243401608], 'avgF1': 0.7129516045890337, 'precision': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6705202312138728], 'avgPrecision': 0.6712112152016477, 'recall': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6705202312138728], 'avgRecall': 0.6712112152016477, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6954022988505747, 0.6896551724137931, 0.7398843930635838, 0.8265895953757225, 0.6820809248554913], 'avgAccuracy': 0.7267224769118331, 'f1': [0.7059289222790964, 0.7165501994765329, 0.7410371632538006, 0.9050632911392403, 0.694201105629824], 'avgF1': 0.7525561363556988, 'precision': [0.6954022988505747, 0.6896551724137931, 0.7398843930635838, 0.8265895953757225, 0.6820809248554913], 'avgPrecision': 0.7267224769118331, 'recall': [0.6954022988505747, 0.6896551724137931, 0.7398843930635838, 0.8265895953757225, 0.6820809248554913], 'avgRecall': 0.7267224769118331, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6091954022988506, 0.6666666666666666, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgAccuracy': 0.5858082519433925, 'f1': [0.6191933347117247, 0.6956140350877194, 0.7178320767658422, 0.40552995391705066, 0.694201105629824], 'avgF1': 0.6264741012224322, 'precision': [0.6091954022988506, 0.6666666666666666, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgPrecision': 0.5858082519433925, 'recall': [0.6091954022988506, 0.6666666666666666, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgRecall': 0.5858082519433925, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.5086705202312138, 0.5664739884393064], 'avgAccuracy': 0.6515580360108962, 'f1': [0.7060784028789387, 0.729883030266172, 0.7813195200729757, 0.6743295019157087, 0.5772928193873451], 'avgF1': 0.693780654904228, 'precision': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.5086705202312138, 0.5664739884393064], 'avgPrecision': 0.6515580360108962, 'recall': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.5086705202312138, 0.5664739884393064], 'avgRecall': 0.6515580360108962, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgAccuracy': 0.6527739020663079, 'f1': [0.6672508525956802, 0.7209330675066161, 0.7122625264118102, 0.7041198501872659, 0.6721740443329903], 'avgF1': 0.6953480682068726, 'precision': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgPrecision': 0.6527739020663079, 'recall': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgRecall': 0.6527739020663079, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6091954022988506, 0.6724137931034483, 0.6936416184971098, 0.10404624277456648, 0.6358381502890174], 'avgAccuracy': 0.5430270413925985, 'f1': [0.6199988947833777, 0.7008585851611275, 0.6949398782108746, 0.18848167539267016, 0.6497628343352881], 'avgF1': 0.5708083735766676, 'precision': [0.6091954022988506, 0.6724137931034483, 0.6936416184971098, 0.10404624277456648, 0.6358381502890174], 'avgPrecision': 0.5430270413925985, 'recall': [0.6091954022988506, 0.6724137931034483, 0.6936416184971098, 0.10404624277456648, 0.6358381502890174], 'avgRecall': 0.5430270413925985, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6149425287356322, 0.6781609195402298, 0.7109826589595376, 0.2658959537572254, 0.6878612716763006], 'avgAccuracy': 0.5915686665337851, 'f1': [0.6252023386379308, 0.7059056678557273, 0.7119772530481384, 0.4200913242009132, 0.6996405085919428], 'avgF1': 0.6325634184669305, 'precision': [0.6149425287356322, 0.6781609195402298, 0.7109826589595376, 0.2658959537572254, 0.6878612716763006], 'avgPrecision': 0.5915686665337851, 'recall': [0.6149425287356322, 0.6781609195402298, 0.7109826589595376, 0.2658959537572254, 0.6878612716763006], 'avgRecall': 0.5915686665337851, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgAccuracy': 0.6527739020663079, 'f1': [0.6672508525956802, 0.7209330675066161, 0.7122625264118102, 0.7041198501872659, 0.6721740443329903], 'avgF1': 0.6953480682068726, 'precision': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgPrecision': 0.6527739020663079, 'recall': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgRecall': 0.6527739020663079, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.671211  0.712952   0.671211  0.671211   
1  0.726722  0.752556   0.726722  0.726722   
2  0.585808  0.626474   0.585808  0.585808   
3  0.589011  0.538441   0.589011  0.589011   
4  0.651558  0.693781   0.651558  0.651558   
5  0.652774  0.695348   0.652774  0.652774   
6  0.543027  0.570808   0.543027  0.543027   
7  0.591569  0.632563   0.591569  0.591569   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6839080459770115, 0.7183908045977011, 0.7572254335260116, 0.5260115606936416, 0.6763005780346821], 'avgAccuracy': 0.6723672845658096, 'f1': [0.6934743841841423, 0.7404758526086751, 0.758206208774358, 0.6893939393939393, 0.6887435437058355], 'avgF1': 0.71405878573339, 'precision': [0.6839080459770115, 0.7183908045977011, 0.7572254335260116, 0.5260115606936416, 0.6763005780346821], 'avgPrecision': 0.6723672845658096, 'recall': [0.6839080459770115, 0.7183908045977011, 0.7572254335260116, 0.5260115606936416, 0.6763005780346821], 'avgRecall': 0.6723672845658096, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6666666666666666, 0.6896551724137931, 0.7572254335260116, 0.8092485549132948, 0.6763005780346821], 'avgAccuracy': 0.7198192811108897, 'f1': [0.6782608695652173, 0.7158616514987058, 0.7583005221859206, 0.8945686900958467, 0.6888813328799728], 'avgF1': 0.7471746132451327, 'precision': [0.6666666666666666, 0.6896551724137931, 0.7572254335260116, 0.8092485549132948, 0.6763005780346821], 'avgPrecision': 0.7198192811108897, 'recall': [0.6666666666666666, 0.6896551724137931, 0.7572254335260116, 0.8092485549132948, 0.6763005780346821], 'avgRecall': 0.7198192811108897, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6149425287356322, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6647398843930635], 'avgAccuracy': 0.5800079728921665, 'f1': [0.6252023386379308, 0.7060520587164044, 0.7058013118092785, 0.38317757009345793, 0.6777699519114003], 'avgF1': 0.6196006462336944, 'precision': [0.6149425287356322, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6647398843930635], 'avgPrecision': 0.5800079728921665, 'recall': [0.6149425287356322, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6647398843930635], 'avgRecall': 0.5800079728921665, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgAccuracy': 0.6816091954022988, 'f1': [0.711544227886057, 0.729883030266172, 0.7755655414866272, 0.6793893129770993, 0.7216046638011956], 'avgF1': 0.7235973552834302, 'precision': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgPrecision': 0.6816091954022988, 'recall': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgRecall': 0.6816091954022988, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6724137931034483, 0.7068965517241379, 0.7456647398843931, 0.49710982658959535, 0.6994219653179191], 'avgAccuracy': 0.6643013753238988, 'f1': [0.6828197573215363, 0.729883030266172, 0.746791023242393, 0.664092664092664, 0.7111040948171177], 'avgF1': 0.7069381139479766, 'precision': [0.6724137931034483, 0.7068965517241379, 0.7456647398843931, 0.49710982658959535, 0.6994219653179191], 'avgPrecision': 0.6643013753238988, 'recall': [0.6724137931034483, 0.7068965517241379, 0.7456647398843931, 0.49710982658959535, 0.6994219653179191], 'avgRecall': 0.6643013753238988, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6091954022988506, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6416184971098265], 'avgAccuracy': 0.5441897548335659, 'f1': [0.6172885281771698, 0.6956140350877194, 0.7006362584825384, 0.18848167539267016, 0.6551957941458886], 'avgF1': 0.5714432582571972, 'precision': [0.6091954022988506, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6416184971098265], 'avgPrecision': 0.5441897548335659, 'recall': [0.6091954022988506, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6416184971098265], 'avgRecall': 0.5441897548335659, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6264367816091954, 0.6954022988505747, 0.7167630057803468, 0.24277456647398843, 0.6705202312138728], 'avgAccuracy': 0.5903793767855956, 'f1': [0.6363903285293359, 0.7215593919778308, 0.7169746279190063, 0.39069767441860465, 0.6832668243401608], 'avgF1': 0.6297777694369877, 'precision': [0.6264367816091954, 0.6954022988505747, 0.7167630057803468, 0.24277456647398843, 0.6705202312138728], 'avgPrecision': 0.5903793767855956, 'recall': [0.6264367816091954, 0.6954022988505747, 0.7167630057803468, 0.24277456647398843, 0.6705202312138728], 'avgRecall': 0.5903793767855956, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgAccuracy': 0.6816091954022988, 'f1': [0.711544227886057, 0.729883030266172, 0.7755655414866272, 0.6793893129770993, 0.7216046638011956], 'avgF1': 0.7235973552834302, 'precision': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgPrecision': 0.6816091954022988, 'recall': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgRecall': 0.6816091954022988, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.672367  0.714059   0.672367  0.672367   
1  0.719819  0.747175   0.719819  0.719819   
2  0.580008  0.619601   0.580008  0.580008   
3  0.589011  0.538441   0.589011  0.589011   
4  0.681609  0.723597   0.681609  0.681609   
5  0.664301  0.706938   0.664301  0.664301   
6  0.544190  0.571443   0.544190  0.544190   
7  0.590379  0.629778   0.590379  0.590379   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6839080459770115, 0.7126436781609196, 0.7630057803468208, 0.49710982658959535, 0.6878612716763006], 'avgAccuracy': 0.6689057205501295, 'f1': [0.6934743841841423, 0.7340820264186416, 0.764010094465016, 0.664092664092664, 0.6996405085919428], 'avgF1': 0.7110599355504813, 'precision': [0.6839080459770115, 0.7126436781609196, 0.7630057803468208, 0.49710982658959535, 0.6878612716763006], 'avgPrecision': 0.6689057205501295, 'recall': [0.6839080459770115, 0.7126436781609196, 0.7630057803468208, 0.49710982658959535, 0.6878612716763006], 'avgRecall': 0.6689057205501295, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6666666666666666, 0.6666666666666666, 0.7572254335260116, 0.7861271676300579, 0.6589595375722543], 'avgAccuracy': 0.7071290944123314, 'f1': [0.6783424908424908, 0.6951566951566953, 0.7583005221859206, 0.8802588996763754, 0.6722583732461128], 'avgF1': 0.736863396221519, 'precision': [0.6666666666666666, 0.6666666666666666, 0.7572254335260116, 0.7861271676300579, 0.6589595375722543], 'avgPrecision': 0.7071290944123314, 'recall': [0.6666666666666666, 0.6666666666666666, 0.7572254335260116, 0.7861271676300579, 0.6589595375722543], 'avgRecall': 0.7071290944123314, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6494252873563219, 0.6839080459770115, 0.6994219653179191, 0.23121387283236994, 0.6878612716763006], 'avgAccuracy': 0.5903660886319846, 'f1': [0.6605387426298953, 0.7110521992222772, 0.700194554963341, 0.37558685446009393, 0.6996405085919428], 'avgF1': 0.6294025719735101, 'precision': [0.6494252873563219, 0.6839080459770115, 0.6994219653179191, 0.23121387283236994, 0.6878612716763006], 'avgPrecision': 0.5903660886319846, 'recall': [0.6494252873563219, 0.6839080459770115, 0.6994219653179191, 0.23121387283236994, 0.6878612716763006], 'avgRecall': 0.5903660886319846, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgAccuracy': 0.6781476313866188, 'f1': [0.7060445027907718, 0.729883030266172, 0.7755655414866272, 0.6692307692307693, 0.7216046638011956], 'avgF1': 0.7204657015151071, 'precision': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgPrecision': 0.6781476313866188, 'recall': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgRecall': 0.6781476313866188, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6666666666666666, 0.7183908045977011, 0.7341040462427746, 0.4682080924855491, 0.6647398843930635], 'avgAccuracy': 0.650421898877151, 'f1': [0.6780891601923789, 0.7410728652814014, 0.7352815242988655, 0.6377952755905512, 0.6777699519114003], 'avgF1': 0.6940017554549195, 'precision': [0.6666666666666666, 0.7183908045977011, 0.7341040462427746, 0.4682080924855491, 0.6647398843930635], 'avgPrecision': 0.650421898877151, 'recall': [0.6666666666666666, 0.7183908045977011, 0.7341040462427746, 0.4682080924855491, 0.6647398843930635], 'avgRecall': 0.650421898877151, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6149425287356322, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6127167630057804], 'avgAccuracy': 0.5395588333001129, 'f1': [0.6243604263556551, 0.6955848928865033, 0.7006362584825384, 0.18848167539267016, 0.6272274267490533], 'avgF1': 0.567258135973284, 'precision': [0.6149425287356322, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6127167630057804], 'avgPrecision': 0.5395588333001129, 'recall': [0.6149425287356322, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6127167630057804], 'avgRecall': 0.5395588333001129, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6494252873563219, 0.6839080459770115, 0.7225433526011561, 0.23121387283236994, 0.6763005780346821], 'avgAccuracy': 0.5926782273603083, 'f1': [0.660035944822963, 0.7113403409850614, 0.7229385363772938, 0.37558685446009393, 0.6887435437058355], 'avgF1': 0.6317290440702495, 'precision': [0.6494252873563219, 0.6839080459770115, 0.7225433526011561, 0.23121387283236994, 0.6763005780346821], 'avgPrecision': 0.5926782273603083, 'recall': [0.6494252873563219, 0.6839080459770115, 0.7225433526011561, 0.23121387283236994, 0.6763005780346821], 'avgRecall': 0.5926782273603083, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgAccuracy': 0.6781476313866188, 'f1': [0.7060445027907718, 0.729883030266172, 0.7755655414866272, 0.6692307692307693, 0.7216046638011956], 'avgF1': 0.7204657015151071, 'precision': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgPrecision': 0.6781476313866188, 'recall': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgRecall': 0.6781476313866188, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.668906  0.711060   0.668906  0.668906   
1  0.707129  0.736863   0.707129  0.707129   
2  0.590366  0.629403   0.590366  0.590366   
3  0.589011  0.538441   0.589011  0.589011   
4  0.678148  0.720466   0.678148  0.678148   
5  0.650422  0.694002   0.650422  0.650422   
6  0.539559  0.567258   0.539559  0.539559   
7  0.592678  0.631729   0.592678  0.592678   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6609195402298851, 0.7068965517241379, 0.7341040462427746, 0.49710982658959535, 0.6820809248554913], 'avgAccuracy': 0.6562221779283769, 'f1': [0.6726378568767298, 0.7314638951478758, 0.7352815242988655, 0.664092664092664, 0.6943802691001552], 'avgF1': 0.699571241903258, 'precision': [0.6609195402298851, 0.7068965517241379, 0.7341040462427746, 0.49710982658959535, 0.6820809248554913], 'avgPrecision': 0.6562221779283769, 'recall': [0.6609195402298851, 0.7068965517241379, 0.7341040462427746, 0.49710982658959535, 0.6820809248554913], 'avgRecall': 0.6562221779283769, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.632183908045977, 0.6724137931034483, 0.7456647398843931, 0.791907514450867, 0.6589595375722543], 'avgAccuracy': 0.700225898611388, 'f1': [0.6435917379656038, 0.7003905678898892, 0.746791023242393, 0.8838709677419355, 0.6722583732461128], 'avgF1': 0.7293805340171868, 'precision': [0.632183908045977, 0.6724137931034483, 0.7456647398843931, 0.791907514450867, 0.6589595375722543], 'avgPrecision': 0.700225898611388, 'recall': [0.632183908045977, 0.6724137931034483, 0.7456647398843931, 0.791907514450867, 0.6589595375722543], 'avgRecall': 0.700225898611388, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.632183908045977, 0.6666666666666666, 0.7109826589595376, 0.24277456647398843, 0.6820809248554913], 'avgAccuracy': 0.5869377450003322, 'f1': [0.6423519009725907, 0.6954685099846389, 0.7104895226282509, 0.39069767441860465, 0.6943802691001552], 'avgF1': 0.626677575420848, 'precision': [0.632183908045977, 0.6666666666666666, 0.7109826589595376, 0.24277456647398843, 0.6820809248554913], 'avgPrecision': 0.5869377450003322, 'recall': [0.632183908045977, 0.6666666666666666, 0.7109826589595376, 0.24277456647398843, 0.6820809248554913], 'avgRecall': 0.5869377450003322, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgAccuracy': 0.6643013753238988, 'f1': [0.6782407407407407, 0.7354959663470932, 0.758206208774358, 0.6431372549019608, 0.7218893598073546], 'avgF1': 0.7073939061143014, 'precision': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgPrecision': 0.6643013753238988, 'recall': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgRecall': 0.6643013753238988, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6494252873563219, 0.6954022988505747, 0.7052023121387283, 0.45664739884393063, 0.6647398843930635], 'avgAccuracy': 0.6342834363165238, 'f1': [0.6616738617025865, 0.7217405838095492, 0.7059513050273538, 0.626984126984127, 0.6777699519114003], 'avgF1': 0.6788239658870033, 'precision': [0.6494252873563219, 0.6954022988505747, 0.7052023121387283, 0.45664739884393063, 0.6647398843930635], 'avgPrecision': 0.6342834363165238, 'recall': [0.6494252873563219, 0.6954022988505747, 0.7052023121387283, 0.45664739884393063, 0.6647398843930635], 'avgRecall': 0.6342834363165238, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.603448275862069, 0.632183908045977, 0.7109826589595376, 0.10404624277456648, 0.6416184971098265], 'avgAccuracy': 0.5384559165503953, 'f1': [0.6111149863635583, 0.6630212769409226, 0.7121502485409023, 0.18848167539267016, 0.6555610784635982], 'avgF1': 0.5660658531403303, 'precision': [0.603448275862069, 0.632183908045977, 0.7109826589595376, 0.10404624277456648, 0.6416184971098265], 'avgPrecision': 0.5384559165503953, 'recall': [0.603448275862069, 0.632183908045977, 0.7109826589595376, 0.10404624277456648, 0.6416184971098265], 'avgRecall': 0.5384559165503953, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.632183908045977, 0.6781609195402298, 0.6994219653179191, 0.24277456647398843, 0.6820809248554913], 'avgAccuracy': 0.5869244568467211, 'f1': [0.6423519009725907, 0.7061101028433151, 0.700194554963341, 0.39069767441860465, 0.6943802691001552], 'avgF1': 0.6267469004596014, 'precision': [0.632183908045977, 0.6781609195402298, 0.6994219653179191, 0.24277456647398843, 0.6820809248554913], 'avgPrecision': 0.5869244568467211, 'recall': [0.632183908045977, 0.6781609195402298, 0.6994219653179191, 0.24277456647398843, 0.6820809248554913], 'avgRecall': 0.5869244568467211, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgAccuracy': 0.6643013753238988, 'f1': [0.6782407407407407, 0.7354959663470932, 0.758206208774358, 0.6431372549019608, 0.7218893598073546], 'avgF1': 0.7073939061143014, 'precision': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgPrecision': 0.6643013753238988, 'recall': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgRecall': 0.6643013753238988, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.656222  0.699571   0.656222  0.656222   
1  0.700226  0.729381   0.700226  0.700226   
2  0.586938  0.626678   0.586938  0.586938   
3  0.589011  0.538441   0.589011  0.589011   
4  0.664301  0.707394   0.664301  0.664301   
5  0.634283  0.678824   0.634283  0.634283   
6  0.538456  0.566066   0.538456  0.538456   
7  0.586924  0.626747   0.586924  0.586924   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6609195402298851, 0.7126436781609196, 0.7398843930635838, 0.47398843930635837, 0.6936416184971098], 'avgAccuracy': 0.6562155338515713, 'f1': [0.6726378568767298, 0.7365278399761159, 0.7410371632538006, 0.6431372549019608, 0.7053210654251031], 'avgF1': 0.6997322360867421, 'precision': [0.6609195402298851, 0.7126436781609196, 0.7398843930635838, 0.47398843930635837, 0.6936416184971098], 'avgPrecision': 0.6562155338515713, 'recall': [0.6609195402298851, 0.7126436781609196, 0.7398843930635838, 0.47398843930635837, 0.6936416184971098], 'avgRecall': 0.6562155338515713, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6436781609195402, 0.6896551724137931, 0.7109826589595376, 0.7803468208092486, 0.6763005780346821], 'avgAccuracy': 0.7001926782273603, 'f1': [0.656151617887214, 0.7165501994765329, 0.7120659903583504, 0.8766233766233766, 0.6889309902629832], 'avgF1': 0.7300644349216914, 'precision': [0.6436781609195402, 0.6896551724137931, 0.7109826589595376, 0.7803468208092486, 0.6763005780346821], 'avgPrecision': 0.7001926782273603, 'recall': [0.6436781609195402, 0.6896551724137931, 0.7109826589595376, 0.7803468208092486, 0.6763005780346821], 'avgRecall': 0.7001926782273603, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6264367816091954, 0.6666666666666666, 0.7052023121387283, 0.23699421965317918, 0.6763005780346821], 'avgAccuracy': 0.5823201116204904, 'f1': [0.6363903285293359, 0.6954685099846389, 0.7049612756344981, 0.38317757009345793, 0.6888813328799728], 'avgF1': 0.6217758034243808, 'precision': [0.6264367816091954, 0.6666666666666666, 0.7052023121387283, 0.23699421965317918, 0.6763005780346821], 'avgPrecision': 0.5823201116204904, 'recall': [0.6264367816091954, 0.6666666666666666, 0.7052023121387283, 0.23699421965317918, 0.6763005780346821], 'avgRecall': 0.5823201116204904, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgAccuracy': 0.6690585343166567, 'f1': [0.609550894655765, 0.6955539179562761, 0.6892435285247549, 0.8729641693811074, 0.633339212558024], 'avgF1': 0.7001303446151854, 'precision': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgPrecision': 0.6690585343166567, 'recall': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgRecall': 0.6690585343166567, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.4797687861271676, 0.7109826589595376], 'avgAccuracy': 0.6654574446880606, 'f1': [0.6782407407407407, 0.7354959663470932, 0.758206208774358, 0.6484375, 0.7218893598073546], 'avgF1': 0.7084539551339093, 'precision': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.4797687861271676, 0.7109826589595376], 'avgPrecision': 0.6654574446880606, 'recall': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.4797687861271676, 0.7109826589595376], 'avgRecall': 0.6654574446880606, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6494252873563219, 0.6781609195402298, 0.7225433526011561, 0.47398843930635837, 0.6705202312138728], 'avgAccuracy': 0.6389276460035878, 'f1': [0.6617128787851937, 0.7060520587164044, 0.7233783946779984, 0.6431372549019608, 0.6828651242491945], 'avgF1': 0.6834291422661504, 'precision': [0.6494252873563219, 0.6781609195402298, 0.7225433526011561, 0.47398843930635837, 0.6705202312138728], 'avgPrecision': 0.6389276460035878, 'recall': [0.6494252873563219, 0.6781609195402298, 0.7225433526011561, 0.47398843930635837, 0.6705202312138728], 'avgRecall': 0.6389276460035878, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6149425287356322, 0.6724137931034483, 0.7109826589595376, 0.09248554913294797, 0.6127167630057804], 'avgAccuracy': 0.5407082585874693, 'f1': [0.6252023386379308, 0.7007868423511822, 0.7121502485409023, 0.1693121693121693, 0.626829637946328], 'avgF1': 0.5668562473577025, 'precision': [0.6149425287356322, 0.6724137931034483, 0.7109826589595376, 0.09248554913294797, 0.6127167630057804], 'avgPrecision': 0.5407082585874693, 'recall': [0.6149425287356322, 0.6724137931034483, 0.7109826589595376, 0.09248554913294797, 0.6127167630057804], 'avgRecall': 0.5407082585874693, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6206896551724138, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6820809248554913], 'avgAccuracy': 0.5846256062720085, 'f1': [0.6303935307496151, 0.7061101028433151, 0.7049612756344981, 0.38317757009345793, 0.6943802691001552], 'avgF1': 0.6238045496842083, 'precision': [0.6206896551724138, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6820809248554913], 'avgPrecision': 0.5846256062720085, 'recall': [0.6206896551724138, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6820809248554913], 'avgRecall': 0.5846256062720085, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgAccuracy': 0.6690585343166567, 'f1': [0.609550894655765, 0.6955539179562761, 0.6892435285247549, 0.8729641693811074, 0.633339212558024], 'avgF1': 0.7001303446151854, 'precision': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgPrecision': 0.6690585343166567, 'recall': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgRecall': 0.6690585343166567, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.656216  0.699732   0.656216  0.656216   
1  0.700193  0.730064   0.700193  0.700193   
2  0.582320  0.621776   0.582320  0.582320   
3  0.669059  0.700130   0.669059  0.669059   
4  0.665457  0.708454   0.665457  0.665457   
5  0.638928  0.683429   0.638928  0.638928   
6  0.540708  0.566856   0.540708  0.540708   
7  0.584626  0.623805   0.584626  0.584626   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

now = datetime.datetime.now()
print ("Current date and time : ")
print (now.strftime("%Y-%m-%d %H:%M:%S"))

Current date and time : 
2021-06-05 10:17:02

# Original Dataset
X2 = pd.concat([X_train_ord, X_test_ord]) #.to_numpy()
y2 = pd.concat([y_train_ord, y_test_ord]).to_numpy()
#data2 = (X2, y2, n_folds)

print('********************************************')
print('Starting Original data set....')
print('********************************************')

for i in range(l ,6 , -1):
    col = []
    col = df[:i]
    nX2 = X2.loc[:, col]
    nX2 = nX2.to_numpy()
    data2 = (nX2, y2, n_folds)
    hyper_search(modelDictionary, modelParamsDictionary, data2, col)

********************************************
Starting Original data set....
********************************************

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7286821705426356, 0.7906976744186046, 0.7674418604651163, 0.7829457364341085, 0.6796875], 'avgAccuracy': 0.749890988372093, 'f1': [0.7163066220090751, 0.7804492770684618, 0.745016611295681, 0.7577327500191879, 0.6551259410725903], 'avgF1': 0.7309262402929992, 'precision': [0.7286821705426356, 0.7906976744186046, 0.7674418604651163, 0.7829457364341085, 0.6796875], 'avgPrecision': 0.749890988372093, 'recall': [0.7286821705426356, 0.7906976744186046, 0.7674418604651163, 0.7829457364341085, 0.6796875], 'avgRecall': 0.749890988372093, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7131782945736435, 0.751937984496124, 0.7984496124031008, 0.7906976744186046, 0.75], 'avgAccuracy': 0.7608527131782946, 'f1': [0.6808189226793878, 0.7418047322288088, 0.7744338668752504, 0.7599524823681759, 0.7285067873303167], 'avgF1': 0.737103358296388, 'precision': [0.7131782945736435, 0.751937984496124, 0.7984496124031008, 0.7906976744186046, 0.75], 'avgPrecision': 0.7608527131782946, 'recall': [0.7131782945736435, 0.751937984496124, 0.7984496124031008, 0.7906976744186046, 0.75], 'avgRecall': 0.7608527131782946, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7131782945736435, 0.8217054263565892, 0.8062015503875969, 0.751937984496124, 0.71875], 'avgAccuracy': 0.7623546511627907, 'f1': [0.6808189226793878, 0.7982676420278779, 0.7697812954980905, 0.6928223031968, 0.65], 'avgF1': 0.7183380326804313, 'precision': [0.7131782945736435, 0.8217054263565892, 0.8062015503875969, 0.751937984496124, 0.71875], 'avgPrecision': 0.7623546511627907, 'recall': [0.7131782945736435, 0.8217054263565892, 0.8062015503875969, 0.751937984496124, 0.71875], 'avgRecall': 0.7623546511627907, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgAccuracy': 0.7484375, 'f1': [0.6098389982110913, 0.7223269781409317, 0.7223269781409317, 0.6606878200386334, 0.6744062389223681], 'avgF1': 0.6779174026907913, 'precision': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgPrecision': 0.7484375, 'recall': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgRecall': 0.7484375, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7131782945736435, 0.7751937984496124, 0.7829457364341085, 0.7906976744186046, 0.734375], 'avgAccuracy': 0.7592781007751938, 'f1': [0.6808189226793878, 0.7558764019683761, 0.7664579606440072, 0.7599524823681759, 0.7163549688302163], 'avgF1': 0.7358921472980327, 'precision': [0.7131782945736435, 0.7751937984496124, 0.7829457364341085, 0.7906976744186046, 0.734375], 'avgPrecision': 0.7592781007751938, 'recall': [0.7131782945736435, 0.7751937984496124, 0.7829457364341085, 0.7906976744186046, 0.734375], 'avgRecall': 0.7592781007751938, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7364341085271318, 0.7286821705426356, 0.7286821705426356, 0.7209302325581395, 0.65625], 'avgAccuracy': 0.7141957364341085, 'f1': [0.7379664683612764, 0.7356029920194277, 0.7196908945104614, 0.7130246958024337, 0.6627033792240301], 'avgF1': 0.7137976859835259, 'precision': [0.7364341085271318, 0.7286821705426356, 0.7286821705426356, 0.7209302325581395, 0.65625], 'avgPrecision': 0.7141957364341085, 'recall': [0.7364341085271318, 0.7286821705426356, 0.7286821705426356, 0.7209302325581395, 0.65625], 'avgRecall': 0.7141957364341085, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7531128875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.677036383162856, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7531128875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7531128875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7654796511627907, 'f1': [0.6808189226793878, 0.780725697856389, 0.7697812954980905, 0.712020909247, 0.7003205128205128], 'avgF1': 0.728733467620276, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7654796511627907, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgRecall': 0.7654796511627907, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7654796511627907, 'f1': [0.6808189226793878, 0.780725697856389, 0.7697812954980905, 0.712020909247, 0.7003205128205128], 'avgF1': 0.728733467620276, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7654796511627907, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgRecall': 0.7654796511627907, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.749891  0.730926   0.749891  0.749891   
1  0.760853  0.737103   0.760853  0.760853   
2  0.762355  0.718338   0.762355  0.762355   
3  0.748437  0.677917   0.748437  0.748437   
4  0.759278  0.735892   0.759278  0.759278   
5  0.714196  0.713798   0.714196  0.714196   
6  0.753113  0.677036   0.753113  0.753113   
7  0.765480  0.728733   0.765480  0.765480   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7674418604651163, 0.6796875], 'avgAccuracy': 0.7514413759689923, 'f1': [0.722972409769109, 0.7868593361932715, 0.7602450484743948, 0.7446672012830794, 0.6551259410725903], 'avgF1': 0.733973987358489, 'precision': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7674418604651163, 0.6796875], 'avgPrecision': 0.7514413759689923, 'recall': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7674418604651163, 0.6796875], 'avgRecall': 0.7514413759689923, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgAccuracy': 0.7655038759689923, 'f1': [0.6808189226793878, 0.7479232440415672, 0.7853697315626679, 0.7710053875124555, 0.7285067873303167], 'avgF1': 0.7427248146252791, 'precision': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgPrecision': 0.7655038759689923, 'recall': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgRecall': 0.7655038759689923, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgAccuracy': 0.759265988372093, 'f1': [0.664364575992483, 0.7697812954980905, 0.7501835985312117, 0.6986158120124709, 0.6546732837055418], 'avgF1': 0.7075237131479596, 'precision': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgPrecision': 0.759265988372093, 'recall': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgRecall': 0.759265988372093, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgAccuracy': 0.7484375, 'f1': [0.6098389982110913, 0.7223269781409317, 0.7223269781409317, 0.6606878200386334, 0.6744062389223681], 'avgF1': 0.6779174026907913, 'precision': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgPrecision': 0.7484375, 'recall': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgRecall': 0.7484375, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgAccuracy': 0.7654796511627907, 'f1': [0.7088378086789738, 0.7558764019683761, 0.77677987271754, 0.7599524823681759, 0.7163549688302163], 'avgF1': 0.7435603069126564, 'precision': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgPrecision': 0.7654796511627907, 'recall': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgRecall': 0.7654796511627907, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7131782945736435, 0.7364341085271318, 0.7131782945736435, 0.6640625], 'avgAccuracy': 0.704905523255814, 'f1': [0.683884521667255, 0.7148013182874647, 0.7332076984763432, 0.7034509662814625, 0.6657672170761176], 'avgF1': 0.7002223443577286, 'precision': [0.6976744186046512, 0.7131782945736435, 0.7364341085271318, 0.7131782945736435, 0.6640625], 'avgPrecision': 0.704905523255814, 'recall': [0.6976744186046512, 0.7131782945736435, 0.7364341085271318, 0.7131782945736435, 0.6640625], 'avgRecall': 0.704905523255814, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7531128875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.677036383162856, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7531128875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7531128875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7623788759689922, 'f1': [0.6745834332294414, 0.7681993100876813, 0.7818383167220376, 0.712020909247, 0.7003205128205128], 'avgF1': 0.7273924964213346, 'precision': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7623788759689922, 'recall': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgRecall': 0.7623788759689922, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7623788759689922, 'f1': [0.6745834332294414, 0.7681993100876813, 0.7818383167220376, 0.712020909247, 0.7003205128205128], 'avgF1': 0.7273924964213346, 'precision': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7623788759689922, 'recall': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgRecall': 0.7623788759689922, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.751441  0.733974   0.751441  0.751441   
1  0.765504  0.742725   0.765504  0.765504   
2  0.759266  0.707524   0.759266  0.759266   
3  0.748437  0.677917   0.748437  0.748437   
4  0.765480  0.743560   0.765480  0.765480   
5  0.704906  0.700222   0.704906  0.704906   
6  0.753113  0.677036   0.753113  0.753113   
7  0.762379  0.727392   0.762379  0.762379   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7364341085271318, 0.8062015503875969, 0.7829457364341085, 0.7751937984496124, 0.6875], 'avgAccuracy': 0.7576550387596899, 'f1': [0.7198911429985156, 0.7933146969606852, 0.762015503875969, 0.7511767965557768, 0.6662999633296663], 'avgF1': 0.7385396207441226, 'precision': [0.7364341085271318, 0.8062015503875969, 0.7829457364341085, 0.7751937984496124, 0.6875], 'avgPrecision': 0.7576550387596899, 'recall': [0.7364341085271318, 0.8062015503875969, 0.7829457364341085, 0.7751937984496124, 0.6875], 'avgRecall': 0.7576550387596899, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgAccuracy': 0.7655038759689923, 'f1': [0.6808189226793878, 0.7479232440415672, 0.7853697315626679, 0.7710053875124555, 0.7285067873303167], 'avgF1': 0.7427248146252791, 'precision': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgPrecision': 0.7655038759689923, 'recall': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgRecall': 0.7655038759689923, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgAccuracy': 0.759265988372093, 'f1': [0.664364575992483, 0.7697812954980905, 0.7501835985312117, 0.6986158120124709, 0.6546732837055418], 'avgF1': 0.7075237131479596, 'precision': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgPrecision': 0.759265988372093, 'recall': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgRecall': 0.759265988372093, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7531128875968992, 'f1': [0.6150153396175428, 0.7223269781409317, 0.7223269781409317, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.6809466545833873, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7531128875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7531128875968992, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgAccuracy': 0.7654796511627907, 'f1': [0.7088378086789738, 0.7558764019683761, 0.77677987271754, 0.7599524823681759, 0.7163549688302163], 'avgF1': 0.7435603069126564, 'precision': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgPrecision': 0.7654796511627907, 'recall': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgRecall': 0.7654796511627907, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7209302325581395, 0.7054263565891473, 0.689922480620155, 0.7829457364341085, 0.640625], 'avgAccuracy': 0.7079699612403101, 'f1': [0.7170891037366083, 0.7115949412610886, 0.6899224806201549, 0.7715825541436906, 0.640625], 'avgF1': 0.7061628159523085, 'precision': [0.7209302325581395, 0.7054263565891473, 0.689922480620155, 0.7829457364341085, 0.640625], 'avgPrecision': 0.7079699612403101, 'recall': [0.7209302325581395, 0.7054263565891473, 0.689922480620155, 0.7829457364341085, 0.640625], 'avgRecall': 0.7079699612403101, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7685804263565892, 'f1': [0.6808189226793878, 0.7870818596747744, 0.7818383167220376, 0.712020909247, 0.6865351629502573], 'avgF1': 0.7296590342546915, 'precision': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7685804263565892, 'recall': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgRecall': 0.7685804263565892, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7685804263565892, 'f1': [0.6808189226793878, 0.7870818596747744, 0.7818383167220376, 0.712020909247, 0.6865351629502573], 'avgF1': 0.7296590342546915, 'precision': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7685804263565892, 'recall': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgRecall': 0.7685804263565892, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.757655  0.738540   0.757655  0.757655   
1  0.765504  0.742725   0.765504  0.765504   
2  0.759266  0.707524   0.759266  0.759266   
3  0.753113  0.680947   0.753113  0.753113   
4  0.765480  0.743560   0.765480  0.765480   
5  0.707970  0.706163   0.707970  0.707970   
6  0.754675  0.678040   0.754675  0.754675   
7  0.768580  0.729659   0.768580  0.768580   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7596899224806202, 0.7906976744186046, 0.7829457364341085, 0.7751937984496124, 0.6796875], 'avgAccuracy': 0.7576429263565891, 'f1': [0.748728722350895, 0.77677987271754, 0.762015503875969, 0.7550893344663139, 0.6606512890094979], 'avgF1': 0.7406529444840432, 'precision': [0.7596899224806202, 0.7906976744186046, 0.7829457364341085, 0.7751937984496124, 0.6796875], 'avgPrecision': 0.7576429263565891, 'recall': [0.7596899224806202, 0.7906976744186046, 0.7829457364341085, 0.7751937984496124, 0.6796875], 'avgRecall': 0.7576429263565891, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7209302325581395, 0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7421875], 'avgAccuracy': 0.7639413759689923, 'f1': [0.6870799332486183, 0.751726220852123, 0.7853697315626679, 0.7599524823681759, 0.7268656716417911], 'avgF1': 0.7421988079346752, 'precision': [0.7209302325581395, 0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7421875], 'avgPrecision': 0.7639413759689923, 'recall': [0.7209302325581395, 0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7421875], 'avgRecall': 0.7639413759689923, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7054263565891473, 0.8062015503875969, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgAccuracy': 0.7654917635658914, 'f1': [0.664364575992483, 0.7697812954980905, 0.7694002447980417, 0.6986158120124709, 0.6836642087351106], 'avgF1': 0.7171652274072393, 'precision': [0.7054263565891473, 0.8062015503875969, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgPrecision': 0.7654917635658914, 'recall': [0.7054263565891473, 0.8062015503875969, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgRecall': 0.7654917635658914, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7531128875968992, 'f1': [0.6150153396175428, 0.7223269781409317, 0.7223269781409317, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.6809466545833873, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7531128875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7531128875968992, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7596899224806202, 0.8449612403100775, 0.7829457364341085, 0.7596899224806202, 0.7109375], 'avgAccuracy': 0.7716448643410853, 'f1': [0.7431053760679646, 0.8331842576028622, 0.762015503875969, 0.7340165756285891, 0.6982720620647096], 'avgF1': 0.7541187550480188, 'precision': [0.7596899224806202, 0.8449612403100775, 0.7829457364341085, 0.7596899224806202, 0.7109375], 'avgPrecision': 0.7716448643410853, 'recall': [0.7596899224806202, 0.8449612403100775, 0.7829457364341085, 0.7596899224806202, 0.7109375], 'avgRecall': 0.7716448643410853, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7674418604651163, 0.7286821705426356, 0.7054263565891473, 0.7286821705426356, 0.671875], 'avgAccuracy': 0.720421511627907, 'f1': [0.764240919780507, 0.733055058636454, 0.7142133544749825, 0.7224406745808836, 0.6598746081504703], 'avgF1': 0.7187649231246594, 'precision': [0.7674418604651163, 0.7286821705426356, 0.7054263565891473, 0.7286821705426356, 0.671875], 'avgPrecision': 0.720421511627907, 'recall': [0.7674418604651163, 0.7286821705426356, 0.7054263565891473, 0.7286821705426356, 0.671875], 'avgRecall': 0.720421511627907, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.7701429263565892, 'f1': [0.6808189226793878, 0.7870818596747744, 0.7818383167220376, 0.7188538205980066, 0.6919423517851294], 'avgF1': 0.7321070542918672, 'precision': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.7701429263565892, 'recall': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgRecall': 0.7701429263565892, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.7701429263565892, 'f1': [0.6808189226793878, 0.7870818596747744, 0.7818383167220376, 0.7188538205980066, 0.6919423517851294], 'avgF1': 0.7321070542918672, 'precision': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.7701429263565892, 'recall': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgRecall': 0.7701429263565892, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.757643  0.740653   0.757643  0.757643   
1  0.763941  0.742199   0.763941  0.763941   
2  0.765492  0.717165   0.765492  0.765492   
3  0.753113  0.680947   0.753113  0.753113   
4  0.771645  0.754119   0.771645  0.771645   
5  0.720422  0.718765   0.720422  0.720422   
6  0.754675  0.678040   0.754675  0.754675   
7  0.770143  0.732107   0.770143  0.770143   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.751937984496124, 0.7829457364341085, 0.7829457364341085, 0.7674418604651163, 0.6796875], 'avgAccuracy': 0.7529917635658915, 'f1': [0.7392681503709261, 0.7704639005158309, 0.762015503875969, 0.7446672012830794, 0.6606512890094979], 'avgF1': 0.7354132090110607, 'precision': [0.751937984496124, 0.7829457364341085, 0.7829457364341085, 0.7674418604651163, 0.6796875], 'avgPrecision': 0.7529917635658915, 'recall': [0.751937984496124, 0.7829457364341085, 0.7829457364341085, 0.7674418604651163, 0.6796875], 'avgRecall': 0.7529917635658915, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7209302325581395, 0.751937984496124, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgAccuracy': 0.7655038759689923, 'f1': [0.6870799332486183, 0.7455346863590013, 0.7853697315626679, 0.7710053875124555, 0.733039970663733], 'avgF1': 0.7444059418692952, 'precision': [0.7209302325581395, 0.751937984496124, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgPrecision': 0.7655038759689923, 'recall': [0.7209302325581395, 0.751937984496124, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgRecall': 0.7655038759689923, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7054263565891473, 0.813953488372093, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgAccuracy': 0.7670421511627907, 'f1': [0.664364575992483, 0.7818383167220376, 0.7694002447980417, 0.6986158120124709, 0.6836642087351106], 'avgF1': 0.7195766316520288, 'precision': [0.7054263565891473, 0.813953488372093, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgPrecision': 0.7670421511627907, 'recall': [0.7054263565891473, 0.813953488372093, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgRecall': 0.7670421511627907, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7546632751937984, 'f1': [0.6150153396175428, 0.7223269781409317, 0.7276790369917914, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.6820170663535592, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7546632751937984, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7546632751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7829457364341085, 0.734375], 'avgAccuracy': 0.774781976744186, 'f1': [0.7363964147673029, 0.7895486223865311, 0.7727125121774536, 0.7486206876588453, 0.7163549688302163], 'avgF1': 0.7527266411640698, 'precision': [0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7829457364341085, 0.734375], 'avgPrecision': 0.774781976744186, 'recall': [0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7829457364341085, 0.734375], 'avgRecall': 0.774781976744186, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7054263565891473, 0.7286821705426356, 0.7441860465116279, 0.7364341085271318, 0.6171875], 'avgAccuracy': 0.7063832364341085, 'f1': [0.7013718317219756, 0.733055058636454, 0.7426608802784123, 0.7259513742071881, 0.622719734660033], 'avgF1': 0.7051517759008126, 'precision': [0.7054263565891473, 0.7286821705426356, 0.7441860465116279, 0.7364341085271318, 0.6171875], 'avgPrecision': 0.7063832364341085, 'recall': [0.7054263565891473, 0.7286821705426356, 0.7441860465116279, 0.7364341085271318, 0.6171875], 'avgRecall': 0.7063832364341085, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.7670421511627907, 'f1': [0.6808189226793878, 0.7681993100876813, 0.7881987918582434, 0.7188538205980066, 0.6919423517851294], 'avgF1': 0.7296026394016897, 'precision': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.7670421511627907, 'recall': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgRecall': 0.7670421511627907, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.7670421511627907, 'f1': [0.6808189226793878, 0.7681993100876813, 0.7881987918582434, 0.7188538205980066, 0.6919423517851294], 'avgF1': 0.7296026394016897, 'precision': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.7670421511627907, 'recall': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgRecall': 0.7670421511627907, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.752992  0.735413   0.752992  0.752992   
1  0.765504  0.744406   0.765504  0.765504   
2  0.767042  0.719577   0.767042  0.767042   
3  0.754663  0.682017   0.754663  0.754663   
4  0.774782  0.752727   0.774782  0.774782   
5  0.706383  0.705152   0.706383  0.706383   
6  0.754675  0.678040   0.754675  0.754675   
7  0.767042  0.729603   0.767042  0.767042   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7596899224806202, 0.7984496124031008, 0.7596899224806202, 0.751937984496124, 0.6953125], 'avgAccuracy': 0.753015988372093, 'f1': [0.748728722350895, 0.7902163449359072, 0.7437102242312496, 0.7276450147019514, 0.6772048846675713], 'avgF1': 0.7375010381775149, 'precision': [0.7596899224806202, 0.7984496124031008, 0.7596899224806202, 0.751937984496124, 0.6953125], 'avgPrecision': 0.753015988372093, 'recall': [0.7596899224806202, 0.7984496124031008, 0.7596899224806202, 0.751937984496124, 0.6953125], 'avgRecall': 0.753015988372093, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7441860465116279, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.7421875], 'avgAccuracy': 0.7701429263565891, 'f1': [0.7108921276253989, 0.751726220852123, 0.780725697856389, 0.7710053875124555, 0.7224184403754995], 'avgF1': 0.7473535748443731, 'precision': [0.7441860465116279, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.7421875], 'avgPrecision': 0.7701429263565891, 'recall': [0.7441860465116279, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.7421875], 'avgRecall': 0.7701429263565891, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7209302325581395, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgAccuracy': 0.7701429263565891, 'f1': [0.6765196471531675, 0.7982676420278779, 0.7694002447980417, 0.6928223031968, 0.6993680884676144], 'avgF1': 0.7272755851287003, 'precision': [0.7209302325581395, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgPrecision': 0.7701429263565891, 'recall': [0.7209302325581395, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgRecall': 0.7701429263565891, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7546632751937984, 'f1': [0.6150153396175428, 0.7223269781409317, 0.7276790369917914, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.6820170663535592, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7546632751937984, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7546632751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7596899224806202, 0.8449612403100775, 0.7674418604651163, 0.751937984496124, 0.7265625], 'avgAccuracy': 0.7701187015503876, 'f1': [0.7534136170908624, 0.8331842576028622, 0.7579419364645084, 0.7276450147019514, 0.7003825920612148], 'avgF1': 0.7545134835842798, 'precision': [0.7596899224806202, 0.8449612403100775, 0.7674418604651163, 0.751937984496124, 0.7265625], 'avgPrecision': 0.7701187015503876, 'recall': [0.7596899224806202, 0.8449612403100775, 0.7674418604651163, 0.751937984496124, 0.7265625], 'avgRecall': 0.7701187015503876, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7054263565891473, 0.7441860465116279, 0.7441860465116279, 0.7751937984496124, 0.640625], 'avgAccuracy': 0.7219234496124031, 'f1': [0.7035077089671531, 0.7483090552857994, 0.7357085576812923, 0.7586565027709453, 0.6366810774858664], 'avgF1': 0.7165725804382113, 'precision': [0.7054263565891473, 0.7441860465116279, 0.7441860465116279, 0.7751937984496124, 0.640625], 'avgPrecision': 0.7219234496124031, 'recall': [0.7054263565891473, 0.7441860465116279, 0.7441860465116279, 0.7751937984496124, 0.640625], 'avgRecall': 0.7219234496124031, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.776344476744186, 'f1': [0.7044643814014727, 0.7998211091234347, 0.7822514111141063, 0.712020909247, 0.6993680884676144], 'avgF1': 0.7395851798707257, 'precision': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.776344476744186, 'recall': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgRecall': 0.776344476744186, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.776344476744186, 'f1': [0.7044643814014727, 0.7998211091234347, 0.7822514111141063, 0.712020909247, 0.6993680884676144], 'avgF1': 0.7395851798707257, 'precision': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.776344476744186, 'recall': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgRecall': 0.776344476744186, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.753016  0.737501   0.753016  0.753016   
1  0.770143  0.747354   0.770143  0.770143   
2  0.770143  0.727276   0.770143  0.770143   
3  0.754663  0.682017   0.754663  0.754663   
4  0.770119  0.754513   0.770119  0.770119   
5  0.721923  0.716573   0.721923  0.721923   
6  0.754675  0.678040   0.754675  0.754675   
7  0.776344  0.739585   0.776344  0.776344   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7596899224806202, 0.6953125], 'avgAccuracy': 0.753015988372093, 'f1': [0.7257877189626429, 0.7902163449359072, 0.7641862605550145, 0.738198943739853, 0.6719490658983177], 'avgF1': 0.738067666818347, 'precision': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7596899224806202, 0.6953125], 'avgPrecision': 0.753015988372093, 'recall': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7596899224806202, 0.6953125], 'avgRecall': 0.753015988372093, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7441860465116279, 0.7596899224806202, 0.7984496124031008, 0.7984496124031008, 0.75], 'avgAccuracy': 0.7701550387596899, 'f1': [0.7108921276253989, 0.751726220852123, 0.7790143964562569, 0.7665763528260706, 0.733039970663733], 'avgF1': 0.7482498136847165, 'precision': [0.7441860465116279, 0.7596899224806202, 0.7984496124031008, 0.7984496124031008, 0.75], 'avgPrecision': 0.7701550387596899, 'recall': [0.7441860465116279, 0.7596899224806202, 0.7984496124031008, 0.7984496124031008, 0.75], 'avgRecall': 0.7701550387596899, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7131782945736435, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgAccuracy': 0.7685925387596899, 'f1': [0.6704274228850202, 0.7982676420278779, 0.7694002447980417, 0.6928223031968, 0.6993680884676144], 'avgF1': 0.7260571402750708, 'precision': [0.7131782945736435, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgPrecision': 0.7685925387596899, 'recall': [0.7131782945736435, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgRecall': 0.7685925387596899, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.751937984496124, 0.8449612403100775, 0.7751937984496124, 0.7286821705426356, 0.734375], 'avgAccuracy': 0.7670300387596899, 'f1': [0.7465315046710396, 0.8331842576028622, 0.7677438840229539, 0.7044181622869307, 0.7062135922330097], 'avgF1': 0.7516182801633592, 'precision': [0.751937984496124, 0.8449612403100775, 0.7751937984496124, 0.7286821705426356, 0.734375], 'avgPrecision': 0.7670300387596899, 'recall': [0.751937984496124, 0.8449612403100775, 0.7751937984496124, 0.7286821705426356, 0.734375], 'avgRecall': 0.7670300387596899, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7286821705426356, 0.7751937984496124, 0.7286821705426356, 0.6744186046511628, 0.671875], 'avgAccuracy': 0.7157703488372092, 'f1': [0.7215960192961348, 0.7788170485844904, 0.7302174632448992, 0.6685799109351804, 0.6682740272697041], 'avgF1': 0.7134968938660818, 'precision': [0.7286821705426356, 0.7751937984496124, 0.7286821705426356, 0.6744186046511628, 0.671875], 'avgPrecision': 0.7157703488372092, 'recall': [0.7286821705426356, 0.7751937984496124, 0.7286821705426356, 0.6744186046511628, 0.671875], 'avgRecall': 0.7157703488372092, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgAccuracy': 0.7732437015503876, 'f1': [0.7044643814014727, 0.7790143964562569, 0.7946447621079583, 0.6986158120124709, 0.6993680884676144], 'avgF1': 0.7352214880891547, 'precision': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgPrecision': 0.7732437015503876, 'recall': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgRecall': 0.7732437015503876, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgAccuracy': 0.7732437015503876, 'f1': [0.7044643814014727, 0.7790143964562569, 0.7946447621079583, 0.6986158120124709, 0.6993680884676144], 'avgF1': 0.7352214880891547, 'precision': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgPrecision': 0.7732437015503876, 'recall': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgRecall': 0.7732437015503876, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.753016  0.738068   0.753016  0.753016   
1  0.770155  0.748250   0.770155  0.770155   
2  0.768593  0.726057   0.768593  0.768593   
3  0.756226  0.681065   0.756226  0.756226   
4  0.767030  0.751618   0.767030  0.767030   
5  0.715770  0.713497   0.715770  0.715770   
6  0.754675  0.678040   0.754675  0.754675   
7  0.773244  0.735221   0.773244  0.773244   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7054263565891473, 0.751937984496124, 0.7596899224806202, 0.7286821705426356, 0.703125], 'avgAccuracy': 0.7297722868217055, 'f1': [0.664364575992483, 0.751937984496124, 0.7145288064176323, 0.6888272919587466, 0.687857142857143], 'avgF1': 0.7015031603444257, 'precision': [0.7054263565891473, 0.751937984496124, 0.7596899224806202, 0.7286821705426356, 0.703125], 'avgPrecision': 0.7297722868217055, 'recall': [0.7054263565891473, 0.751937984496124, 0.7596899224806202, 0.7286821705426356, 0.703125], 'avgRecall': 0.7297722868217055, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6976744186046512, 0.7286821705426356, 0.7674418604651163, 0.8372093023255814, 0.6953125], 'avgAccuracy': 0.7452640503875969, 'f1': [0.658327059920926, 0.733055058636454, 0.7579419364645084, 0.825234019247926, 0.6661406025824965], 'avgF1': 0.7281397353704622, 'precision': [0.6976744186046512, 0.7286821705426356, 0.7674418604651163, 0.8372093023255814, 0.6953125], 'avgPrecision': 0.7452640503875969, 'recall': [0.6976744186046512, 0.7286821705426356, 0.7674418604651163, 0.8372093023255814, 0.6953125], 'avgRecall': 0.7452640503875969, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgAccuracy': 0.7639656007751938, 'f1': [0.6705042597282984, 0.7443820913078638, 0.7421607654165794, 0.6928223031968, 0.6941391941391942], 'avgF1': 0.7088017227577472, 'precision': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgPrecision': 0.7639656007751938, 'recall': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgRecall': 0.7639656007751938, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7209302325581395, 0.703125], 'avgAccuracy': 0.740625, 'f1': [0.6683696830943487, 0.7443820913078638, 0.7276790369917914, 0.6700536672629696, 0.6776018099547512], 'avgF1': 0.697617257722345, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7209302325581395, 0.703125], 'avgPrecision': 0.740625, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7209302325581395, 0.703125], 'avgRecall': 0.740625, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7131782945736435, 0.751937984496124, 0.7131782945736435, 0.6589147286821705, 0.640625], 'avgAccuracy': 0.6955668604651163, 'f1': [0.6853763660125872, 0.7593375616631429, 0.7036732313396307, 0.6311800172265288, 0.640625], 'avgF1': 0.6840384352483779, 'precision': [0.7131782945736435, 0.751937984496124, 0.7131782945736435, 0.6589147286821705, 0.640625], 'avgPrecision': 0.6955668604651163, 'recall': [0.7131782945736435, 0.751937984496124, 0.7131782945736435, 0.6589147286821705, 0.640625], 'avgRecall': 0.6955668604651163, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7131782945736435, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgAccuracy': 0.7624152131782945, 'f1': [0.6758487491557502, 0.7443820913078638, 0.7421607654165794, 0.6928223031968, 0.6941391941391942], 'avgF1': 0.7098706206432376, 'precision': [0.7131782945736435, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgPrecision': 0.7624152131782945, 'recall': [0.7131782945736435, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgRecall': 0.7624152131782945, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgAccuracy': 0.7639656007751938, 'f1': [0.6705042597282984, 0.7443820913078638, 0.7421607654165794, 0.6928223031968, 0.6941391941391942], 'avgF1': 0.7088017227577472, 'precision': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgPrecision': 0.7639656007751938, 'recall': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgRecall': 0.7639656007751938, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.729772  0.701503   0.729772  0.729772   
1  0.745264  0.728140   0.745264  0.745264   
2  0.763966  0.708802   0.763966  0.763966   
3  0.756226  0.681065   0.756226  0.756226   
4  0.740625  0.697617   0.740625  0.740625   
5  0.695567  0.684038   0.695567  0.695567   
6  0.754675  0.678040   0.754675  0.754675   
7  0.762415  0.709871   0.762415  0.762415   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7441860465116279, 0.7751937984496124, 0.7364341085271318, 0.6953125], 'avgAccuracy': 0.7297601744186046, 'f1': [0.658327059920926, 0.7456336082023335, 0.7254474314047425, 0.6947536921571692, 0.6719490658983177], 'avgF1': 0.6992221715166977, 'precision': [0.6976744186046512, 0.7441860465116279, 0.7751937984496124, 0.7364341085271318, 0.6953125], 'avgPrecision': 0.7297601744186046, 'recall': [0.6976744186046512, 0.7441860465116279, 0.7751937984496124, 0.7364341085271318, 0.6953125], 'avgRecall': 0.7297601744186046, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7054263565891473, 0.7751937984496124, 0.7751937984496124, 0.7674418604651163, 0.71875], 'avgAccuracy': 0.7484011627906977, 'f1': [0.6452601712519633, 0.7329463027777849, 0.739643050297458, 0.7044614807057755, 0.6889320388349514], 'avgF1': 0.7022486087735866, 'precision': [0.7054263565891473, 0.7751937984496124, 0.7751937984496124, 0.7674418604651163, 0.71875], 'avgPrecision': 0.7484011627906977, 'recall': [0.7054263565891473, 0.7751937984496124, 0.7751937984496124, 0.7674418604651163, 0.71875], 'avgRecall': 0.7484011627906977, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 15, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgAccuracy': 0.7639656007751938, 'f1': [0.6705042597282984, 0.7443820913078638, 0.7421607654165794, 0.6928223031968, 0.6941391941391942], 'avgF1': 0.7088017227577472, 'precision': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgPrecision': 0.7639656007751938, 'recall': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgRecall': 0.7639656007751938, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6683696830943487, 0.7443820913078638, 0.7478509601775845, 0.6700536672629696, 0.7083333333333335], 'avgF1': 0.70779794703522, 'precision': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6589147286821705, 0.7441860465116279, 0.7286821705426356, 0.7131782945736435, 0.6640625], 'avgAccuracy': 0.7018047480620155, 'f1': [0.6283914728682171, 0.7528617717451948, 0.7270645699922553, 0.6825359128470256, 0.6657672170761176], 'avgF1': 0.6913241889057621, 'precision': [0.6589147286821705, 0.7441860465116279, 0.7286821705426356, 0.7131782945736435, 0.6640625], 'avgPrecision': 0.7018047480620155, 'recall': [0.6589147286821705, 0.7441860465116279, 0.7286821705426356, 0.7131782945736435, 0.6640625], 'avgRecall': 0.7018047480620155, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgAccuracy': 0.7639898255813954, 'f1': [0.6580489278163697, 0.7443820913078638, 0.7276790369917914, 0.6847589127528272, 0.7220079410096427], 'avgF1': 0.7073753819756989, 'precision': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgPrecision': 0.7639898255813954, 'recall': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgRecall': 0.7639898255813954, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgAccuracy': 0.7639898255813954, 'f1': [0.6580489278163697, 0.7443820913078638, 0.7276790369917914, 0.6847589127528272, 0.7220079410096427], 'avgF1': 0.7073753819756989, 'precision': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgPrecision': 0.7639898255813954, 'recall': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgRecall': 0.7639898255813954, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.729760  0.699222   0.729760  0.729760   
1  0.748401  0.702249   0.748401  0.748401   
2  0.763966  0.708802   0.763966  0.763966   
3  0.756226  0.681065   0.756226  0.756226   
4  0.756226  0.707798   0.756226  0.756226   
5  0.701805  0.691324   0.701805  0.701805   
6  0.754675  0.678040   0.754675  0.754675   
7  0.763990  0.707375   0.763990  0.763990   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7131782945736435, 0.7441860465116279, 0.7674418604651163, 0.7286821705426356, 0.6796875], 'avgAccuracy': 0.7266351744186047, 'f1': [0.6758487491557502, 0.7456336082023335, 0.7199701301472157, 0.6888272919587466, 0.6656528255311646], 'avgF1': 0.6991865209990421, 'precision': [0.7131782945736435, 0.7441860465116279, 0.7674418604651163, 0.7286821705426356, 0.6796875], 'avgPrecision': 0.7266351744186047, 'recall': [0.7131782945736435, 0.7441860465116279, 0.7674418604651163, 0.7286821705426356, 0.6796875], 'avgRecall': 0.7266351744186047, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7364341085271318, 0.7906976744186046, 0.7596899224806202, 0.7596899224806202, 0.734375], 'avgAccuracy': 0.7561773255813954, 'f1': [0.7405131044665928, 0.7513637991379379, 0.6975037754791518, 0.6903912024517757, 0.7246603970741902], 'avgF1': 0.7208864557219297, 'precision': [0.7364341085271318, 0.7906976744186046, 0.7596899224806202, 0.7596899224806202, 0.734375], 'avgPrecision': 0.7561773255813954, 'recall': [0.7364341085271318, 0.7906976744186046, 0.7596899224806202, 0.7596899224806202, 0.734375], 'avgRecall': 0.7561773255813954, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7209302325581395, 0.7906976744186046, 0.8062015503875969, 0.751937984496124, 0.7578125], 'avgAccuracy': 0.765515988372093, 'f1': [0.6705042597282984, 0.7443820913078638, 0.7560514318380255, 0.6928223031968, 0.6941391941391942], 'avgF1': 0.7115798560420364, 'precision': [0.7209302325581395, 0.7906976744186046, 0.8062015503875969, 0.751937984496124, 0.7578125], 'avgPrecision': 0.765515988372093, 'recall': [0.7209302325581395, 0.7906976744186046, 0.8062015503875969, 0.751937984496124, 0.7578125], 'avgRecall': 0.765515988372093, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6683696830943487, 0.7443820913078638, 0.7478509601775845, 0.6700536672629696, 0.7083333333333335], 'avgF1': 0.70779794703522, 'precision': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6821705426356589, 0.7054263565891473, 0.7286821705426356, 0.6666666666666666, 0.703125], 'avgAccuracy': 0.6972141472868217, 'f1': [0.6559931379265853, 0.7142133544749825, 0.7053680713411435, 0.6310552500654623, 0.6962585034013606], 'avgF1': 0.6805776634419068, 'precision': [0.6821705426356589, 0.7054263565891473, 0.7286821705426356, 0.6666666666666666, 0.703125], 'avgPrecision': 0.6972141472868217, 'recall': [0.6821705426356589, 0.7054263565891473, 0.7286821705426356, 0.6666666666666666, 0.703125], 'avgRecall': 0.6972141472868217, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgAccuracy': 0.767078488372093, 'f1': [0.6826455239104355, 0.7386387881374012, 0.7560514318380255, 0.6847589127528272, 0.7083333333333335], 'avgF1': 0.7140855979944046, 'precision': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgPrecision': 0.767078488372093, 'recall': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgRecall': 0.767078488372093, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgAccuracy': 0.767078488372093, 'f1': [0.6826455239104355, 0.7386387881374012, 0.7560514318380255, 0.6847589127528272, 0.7083333333333335], 'avgF1': 0.7140855979944046, 'precision': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgPrecision': 0.767078488372093, 'recall': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgRecall': 0.767078488372093, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.726635  0.699187   0.726635  0.726635   
1  0.756177  0.720886   0.756177  0.756177   
2  0.765516  0.711580   0.765516  0.765516   
3  0.756226  0.681065   0.756226  0.756226   
4  0.756226  0.707798   0.756226  0.756226   
5  0.697214  0.680578   0.697214  0.697214   
6  0.754675  0.678040   0.754675  0.754675   
7  0.767078  0.714086   0.767078  0.767078   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.689922480620155, 0.8062015503875969, 0.7829457364341085, 0.7054263565891473, 0.7578125], 'avgAccuracy': 0.7484617248062015, 'f1': [0.6405773857257417, 0.7633167512109851, 0.7309669522643819, 0.6517233154442457, 0.7028360748723765], 'avgF1': 0.6978840959035462, 'precision': [0.689922480620155, 0.8062015503875969, 0.7829457364341085, 0.7054263565891473, 0.7578125], 'avgPrecision': 0.7484617248062015, 'recall': [0.689922480620155, 0.8062015503875969, 0.7829457364341085, 0.7054263565891473, 0.7578125], 'avgRecall': 0.7484617248062015, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.689922480620155, 0.7751937984496124, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgAccuracy': 0.7531371124031008, 'f1': [0.6002214839424141, 0.707507113805998, 0.7176321353065539, 0.6555514540010664, 0.6944408532643827], 'avgF1': 0.675070608064083, 'precision': [0.689922480620155, 0.7751937984496124, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgPrecision': 0.7531371124031008, 'recall': [0.689922480620155, 0.7751937984496124, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgRecall': 0.7531371124031008, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 15, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7577640503875969, 'f1': [0.664364575992483, 0.7309669522643819, 0.7330833496189173, 0.6606878200386334, 0.6941391941391942], 'avgF1': 0.6966483784107219, 'precision': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7577640503875969, 'recall': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7577640503875969, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6853763660125872, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.714847219077563, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6666666666666666, 0.751937984496124, 0.7286821705426356, 0.6434108527131783, 0.765625], 'avgAccuracy': 0.7112645348837209, 'f1': [0.6392123153864188, 0.7376730291609497, 0.6930159769989446, 0.6144154725550075, 0.7234133790737565], 'avgF1': 0.6815460346350154, 'precision': [0.6666666666666666, 0.751937984496124, 0.7286821705426356, 0.6434108527131783, 0.765625], 'avgPrecision': 0.7112645348837209, 'recall': [0.6666666666666666, 0.751937984496124, 0.7286821705426356, 0.6434108527131783, 0.765625], 'avgRecall': 0.7112645348837209, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7593265503875969, 'f1': [0.664364575992483, 0.7309669522643819, 0.7330833496189173, 0.6606878200386334, 0.7162883845126836], 'avgF1': 0.7010782164854198, 'precision': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7593265503875969, 'recall': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgRecall': 0.7593265503875969, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6853763660125872, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.714847219077563, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.748462  0.697884   0.748462  0.748462   
1  0.753137  0.675071   0.753137  0.753137   
2  0.757764  0.696648   0.757764  0.757764   
3  0.756226  0.681065   0.756226  0.756226   
4  0.763953  0.714847   0.763953  0.763953   
5  0.711265  0.681546   0.711265  0.711265   
6  0.754675  0.678040   0.754675  0.754675   
7  0.759327  0.701078   0.759327  0.759327   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.689922480620155, 0.7906976744186046, 0.7829457364341085, 0.7054263565891473, 0.7421875], 'avgAccuracy': 0.7422359496124031, 'f1': [0.6405773857257417, 0.7513637991379379, 0.7223269781409317, 0.6438815060908084, 0.6744062389223681], 'avgF1': 0.6865111816035576, 'precision': [0.689922480620155, 0.7906976744186046, 0.7829457364341085, 0.7054263565891473, 0.7421875], 'avgPrecision': 0.7422359496124031, 'recall': [0.689922480620155, 0.7906976744186046, 0.7829457364341085, 0.7054263565891473, 0.7421875], 'avgRecall': 0.7422359496124031, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgAccuracy': 0.7546875, 'f1': [0.6002214839424141, 0.7223269781409317, 0.7176321353065539, 0.6555514540010664, 0.6944408532643827], 'avgF1': 0.6780345809310697, 'precision': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgPrecision': 0.7546875, 'recall': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgRecall': 0.7546875, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 15, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7593144379844962, 'f1': [0.664364575992483, 0.7365355463850676, 0.7330833496189173, 0.6606878200386334, 0.6941391941391942], 'avgF1': 0.697762097234859, 'precision': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7593144379844962, 'recall': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7593144379844962, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6853763660125872, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.714847219077563, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6744186046511628, 0.751937984496124, 0.7441860465116279, 0.6511627906976745, 0.7265625], 'avgAccuracy': 0.7096535852713178, 'f1': [0.6498236014111888, 0.7280177187153931, 0.7222041815502211, 0.6199662086546249, 0.6644923425978446], 'avgF1': 0.6769008105858545, 'precision': [0.6744186046511628, 0.751937984496124, 0.7441860465116279, 0.6511627906976745, 0.7265625], 'avgPrecision': 0.7096535852713178, 'recall': [0.6744186046511628, 0.751937984496124, 0.7441860465116279, 0.6511627906976745, 0.7265625], 'avgRecall': 0.7096535852713178, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7593265503875969, 'f1': [0.658327059920926, 0.7365355463850676, 0.7330833496189173, 0.6606878200386334, 0.7162883845126836], 'avgF1': 0.7009844320952455, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7593265503875969, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgRecall': 0.7593265503875969, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6853763660125872, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.714847219077563, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.742236  0.686511   0.742236  0.742236   
1  0.754687  0.678035   0.754687  0.754687   
2  0.759314  0.697762   0.759314  0.759314   
3  0.756226  0.681065   0.756226  0.756226   
4  0.763953  0.714847   0.763953  0.763953   
5  0.709654  0.676901   0.709654  0.709654   
6  0.754675  0.678040   0.754675  0.754675   
7  0.759327  0.700984   0.759327  0.759327   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.689922480620155, 0.7906976744186046, 0.751937984496124, 0.6821705426356589, 0.7578125], 'avgAccuracy': 0.7345082364341086, 'f1': [0.6338936219203315, 0.7513637991379379, 0.7013014721570301, 0.6281603080508689, 0.7028360748723765], 'avgF1': 0.6835110552277089, 'precision': [0.689922480620155, 0.7906976744186046, 0.751937984496124, 0.6821705426356589, 0.7578125], 'avgPrecision': 0.7345082364341086, 'recall': [0.689922480620155, 0.7906976744186046, 0.751937984496124, 0.6821705426356589, 0.7578125], 'avgRecall': 0.7345082364341086, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgAccuracy': 0.7546875, 'f1': [0.6002214839424141, 0.7309669522643819, 0.7176321353065539, 0.6736236971466001, 0.6944408532643827], 'avgF1': 0.6833770243848666, 'precision': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgPrecision': 0.7546875, 'recall': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgRecall': 0.7546875, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 15, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7593144379844962, 'f1': [0.664364575992483, 0.7365355463850676, 0.7330833496189173, 0.6606878200386334, 0.6941391941391942], 'avgF1': 0.697762097234859, 'precision': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7593144379844962, 'recall': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7593144379844962, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6808189226793878, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.7139357304109232, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6976744186046512, 0.7674418604651163, 0.751937984496124, 0.6976744186046512, 0.71875], 'avgAccuracy': 0.7266957364341086, 'f1': [0.6727739604667519, 0.7397313848560582, 0.7161091462330323, 0.6532646967540319, 0.6826923076923077], 'avgF1': 0.6929142992004363, 'precision': [0.6976744186046512, 0.7674418604651163, 0.751937984496124, 0.6976744186046512, 0.71875], 'avgPrecision': 0.7266957364341086, 'recall': [0.6976744186046512, 0.7674418604651163, 0.751937984496124, 0.6976744186046512, 0.71875], 'avgRecall': 0.7266957364341086, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.658327059920926, 0.7443820913078638, 0.7276790369917914, 0.6555514540010664, 0.7162883845126836], 'avgF1': 0.7004456053468663, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7364341085271318, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6808189226793878, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.7139357304109232, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.734508  0.683511   0.734508  0.734508   
1  0.754687  0.683377   0.754687  0.754687   
2  0.759314  0.697762   0.759314  0.759314   
3  0.756226  0.681065   0.756226  0.756226   
4  0.763953  0.713936   0.763953  0.763953   
5  0.726696  0.692914   0.726696  0.726696   
6  0.754675  0.678040   0.754675  0.754675   
7  0.756226  0.700446   0.756226  0.756226   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7441860465116279, 0.7286821705426356, 0.7578125], 'avgAccuracy': 0.7438105620155039, 'f1': [0.658327059920926, 0.7575987020010818, 0.6961113100574797, 0.6597275296914996, 0.7175882043180621], 'avgF1': 0.6978705611978099, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7441860465116279, 0.7286821705426356, 0.7578125], 'avgPrecision': 0.7438105620155039, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7441860465116279, 0.7286821705426356, 0.7578125], 'avgRecall': 0.7438105620155039, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6821705426356589, 0.7829457364341085, 0.7829457364341085, 0.751937984496124, 0.78125], 'avgAccuracy': 0.75625, 'f1': [0.6408053706861018, 0.7454780361757106, 0.7125512995896034, 0.6928223031968, 0.7194591984548527], 'avgF1': 0.7022232416206137, 'precision': [0.6821705426356589, 0.7829457364341085, 0.7829457364341085, 0.751937984496124, 0.78125], 'avgPrecision': 0.75625, 'recall': [0.6821705426356589, 0.7829457364341085, 0.7829457364341085, 0.751937984496124, 0.78125], 'avgRecall': 0.75625, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7608769379844961, 'f1': [0.664364575992483, 0.7365355463850676, 0.7330833496189173, 0.6606878200386334, 0.7162883845126836], 'avgF1': 0.7021919353095569, 'precision': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7608769379844961, 'recall': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgRecall': 0.7608769379844961, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgAccuracy': 0.7608648255813953, 'f1': [0.6808189226793878, 0.7697812954980905, 0.7501835985312117, 0.6756955814483354, 0.7175882043180621], 'avgF1': 0.7188135204950176, 'precision': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgPrecision': 0.7608648255813953, 'recall': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgRecall': 0.7608648255813953, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6976744186046512, 0.7441860465116279, 0.751937984496124, 0.6434108527131783, 0.7734375], 'avgAccuracy': 0.7221293604651163, 'f1': [0.6683696830943487, 0.7222041815502211, 0.7161091462330323, 0.6198182198610876, 0.7599728629579376], 'avgF1': 0.6972948187393255, 'precision': [0.6976744186046512, 0.7441860465116279, 0.751937984496124, 0.6434108527131783, 0.7734375], 'avgPrecision': 0.7221293604651163, 'recall': [0.6976744186046512, 0.7441860465116279, 0.751937984496124, 0.6434108527131783, 0.7734375], 'avgRecall': 0.7221293604651163, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7054263565891473, 0.7751937984496124, 0.8062015503875969, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7577761627906977, 'f1': [0.664364575992483, 0.7329463027777849, 0.7560514318380255, 0.6555514540010664, 0.7162883845126836], 'avgF1': 0.7050404298244087, 'precision': [0.7054263565891473, 0.7751937984496124, 0.8062015503875969, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7577761627906977, 'recall': [0.7054263565891473, 0.7751937984496124, 0.8062015503875969, 0.7364341085271318, 0.765625], 'avgRecall': 0.7577761627906977, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgAccuracy': 0.7608648255813953, 'f1': [0.6808189226793878, 0.7697812954980905, 0.7501835985312117, 0.6756955814483354, 0.7175882043180621], 'avgF1': 0.7188135204950176, 'precision': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgPrecision': 0.7608648255813953, 'recall': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgRecall': 0.7608648255813953, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.743811  0.697871   0.743811  0.743811   
1  0.756250  0.702223   0.756250  0.756250   
2  0.760877  0.702192   0.760877  0.760877   
3  0.756226  0.681065   0.756226  0.756226   
4  0.760865  0.718814   0.760865  0.760865   
5  0.722129  0.697295   0.722129  0.722129   
6  0.754675  0.678040   0.754675  0.754675   
7  0.757776  0.705040   0.757776  0.757776   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.7674418604651163, 0.7209302325581395, 0.7578125], 'avgAccuracy': 0.7484617248062015, 'f1': [0.6585485164394547, 0.7443820913078638, 0.7199701301472157, 0.662624584717608, 0.7175882043180621], 'avgF1': 0.7006227053860409, 'precision': [0.7054263565891473, 0.7906976744186046, 0.7674418604651163, 0.7209302325581395, 0.7578125], 'avgPrecision': 0.7484617248062015, 'recall': [0.7054263565891473, 0.7906976744186046, 0.7674418604651163, 0.7209302325581395, 0.7578125], 'avgRecall': 0.7484617248062015, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6821705426356589, 0.7829457364341085, 0.7906976744186046, 0.751937984496124, 0.78125], 'avgAccuracy': 0.7578003875968992, 'f1': [0.6408053706861018, 0.7386387881374012, 0.7276790369917914, 0.6928223031968, 0.7194591984548527], 'avgF1': 0.7038809394933895, 'precision': [0.6821705426356589, 0.7829457364341085, 0.7906976744186046, 0.751937984496124, 0.78125], 'avgPrecision': 0.7578003875968992, 'recall': [0.6821705426356589, 0.7829457364341085, 0.7906976744186046, 0.751937984496124, 0.78125], 'avgRecall': 0.7578003875968992, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7608769379844961, 'f1': [0.664364575992483, 0.7421607654165794, 0.7330833496189173, 0.6555514540010664, 0.7162883845126836], 'avgF1': 0.7022897059083459, 'precision': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7608769379844961, 'recall': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgRecall': 0.7608769379844961, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7364341085271318, 0.75], 'avgAccuracy': 0.7515503875968992, 'f1': [0.6727739604667519, 0.7513637991379379, 0.7223269781409317, 0.6813676633444076, 0.7118012422360248], 'avgF1': 0.7079267286652108, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7364341085271318, 0.75], 'avgPrecision': 0.7515503875968992, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7364341085271318, 0.75], 'avgRecall': 0.7515503875968992, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7054263565891473, 0.7596899224806202, 0.7364341085271318, 0.6666666666666666, 0.7578125], 'avgAccuracy': 0.7252059108527131, 'f1': [0.664364575992483, 0.7390402917592985, 0.7110188261351053, 0.6513617643151322, 0.734624581539933], 'avgF1': 0.7000820079483904, 'precision': [0.7054263565891473, 0.7596899224806202, 0.7364341085271318, 0.6666666666666666, 0.7578125], 'avgPrecision': 0.7252059108527131, 'recall': [0.7054263565891473, 0.7596899224806202, 0.7364341085271318, 0.6666666666666666, 0.7578125], 'avgRecall': 0.7252059108527131, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7593265503875969, 'f1': [0.658327059920926, 0.7421607654165794, 0.7330833496189173, 0.6555514540010664, 0.7162883845126836], 'avgF1': 0.7010822026940345, 'precision': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7593265503875969, 'recall': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgRecall': 0.7593265503875969, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7608769379844961, 'f1': [0.664364575992483, 0.7421607654165794, 0.7330833496189173, 0.6555514540010664, 0.7162883845126836], 'avgF1': 0.7022897059083459, 'precision': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7608769379844961, 'recall': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgRecall': 0.7608769379844961, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.748462  0.700623   0.748462  0.748462   
1  0.757800  0.703881   0.757800  0.757800   
2  0.760877  0.702290   0.760877  0.760877   
3  0.756226  0.681065   0.756226  0.756226   
4  0.751550  0.707927   0.751550  0.751550   
5  0.725206  0.700082   0.725206  0.725206   
6  0.754675  0.678040   0.754675  0.754675   
7  0.759327  0.701082   0.759327  0.759327   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.8062015503875969, 0.7441860465116279, 0.689922480620155, 0.765625], 'avgAccuracy': 0.7407218992248062, 'f1': [0.6635658914728682, 0.7755543537047053, 0.7037317468902109, 0.6333929636255217, 0.7355769230769231], 'avgF1': 0.7023643757540459, 'precision': [0.6976744186046512, 0.8062015503875969, 0.7441860465116279, 0.689922480620155, 0.765625], 'avgPrecision': 0.7407218992248062, 'recall': [0.6976744186046512, 0.8062015503875969, 0.7441860465116279, 0.689922480620155, 0.765625], 'avgRecall': 0.7407218992248062, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.813953488372093, 0.7674418604651163, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.7063172311088063, 0.7694002447980417, 0.7024931908652838, 0.6813676633444076, 0.7234133790737565], 'avgF1': 0.7165983418380591, 'precision': [0.6976744186046512, 0.813953488372093, 0.7674418604651163, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.813953488372093, 0.7674418604651163, 0.7364341085271318, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7593144379844962, 'f1': [0.658327059920926, 0.7501835985312117, 0.7330833496189173, 0.6606878200386334, 0.7175882043180621], 'avgF1': 0.7039740064855501, 'precision': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7593144379844962, 'recall': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7593144379844962, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.689922480620155, 0.8062015503875969, 0.7751937984496124, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6664986680106559, 0.7633167512109851, 0.7170196609321097, 0.6813676633444076, 0.7234133790737565], 'avgF1': 0.7103232245143829, 'precision': [0.689922480620155, 0.8062015503875969, 0.7751937984496124, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.689922480620155, 0.8062015503875969, 0.7751937984496124, 0.7364341085271318, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7751937984496124, 0.7131782945736435, 0.6821705426356589, 0.765625], 'avgAccuracy': 0.7267684108527132, 'f1': [0.6683696830943487, 0.7558764019683761, 0.6823472027127483, 0.6587902280554744, 0.745475113122172], 'avgF1': 0.7021717257906239, 'precision': [0.6976744186046512, 0.7751937984496124, 0.7131782945736435, 0.6821705426356589, 0.765625], 'avgPrecision': 0.7267684108527132, 'recall': [0.6976744186046512, 0.7751937984496124, 0.7131782945736435, 0.6821705426356589, 0.765625], 'avgRecall': 0.7267684108527132, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7608769379844961, 'f1': [0.658327059920926, 0.7501835985312117, 0.7330833496189173, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6983351535007255, 'precision': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7608769379844961, 'recall': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgRecall': 0.7608769379844961, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7608769379844961, 'f1': [0.658327059920926, 0.7501835985312117, 0.7330833496189173, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6983351535007255, 'precision': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7608769379844961, 'recall': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgRecall': 0.7608769379844961, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.740722  0.702364   0.740722  0.740722   
1  0.756226  0.716598   0.756226  0.756226   
2  0.759314  0.703974   0.759314  0.759314   
3  0.756226  0.681065   0.756226  0.756226   
4  0.754675  0.710323   0.754675  0.754675   
5  0.726768  0.702172   0.726768  0.726768   
6  0.754675  0.678040   0.754675  0.754675   
7  0.760877  0.698335   0.760877  0.760877   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6976744186046512, 0.813953488372093, 0.751937984496124, 0.6976744186046512, 0.765625], 'avgAccuracy': 0.7453730620155039, 'f1': [0.6635658914728682, 0.7818383167220376, 0.7091177556293835, 0.6596027869484165, 0.7355769230769231], 'avgF1': 0.7099403347699258, 'precision': [0.6976744186046512, 0.813953488372093, 0.751937984496124, 0.6976744186046512, 0.765625], 'avgPrecision': 0.7453730620155039, 'recall': [0.6976744186046512, 0.813953488372093, 0.751937984496124, 0.6976744186046512, 0.765625], 'avgRecall': 0.7453730620155039, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6976744186046512, 0.813953488372093, 0.7596899224806202, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.7070291844805862, 0.7694002447980417, 0.6975037754791518, 0.6813676633444076, 0.7234133790737565], 'avgF1': 0.7157428494351887, 'precision': [0.6976744186046512, 0.813953488372093, 0.7596899224806202, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.813953488372093, 0.7596899224806202, 0.7364341085271318, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7562136627906977, 'f1': [0.658327059920926, 0.7125512995896034, 0.7330833496189173, 0.6606878200386334, 0.7175882043180621], 'avgF1': 0.6964475466972284, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7562136627906977, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7562136627906977, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6666666666666666, 0.6589147286821705, 0.6821705426356589, 0.7596899224806202, 0.6171875], 'avgAccuracy': 0.6769258720930232, 'f1': [0.676594962309248, 0.6841180738534388, 0.7035224968465439, 0.7653217970740854, 0.6417397809970754], 'avgF1': 0.6942594222160783, 'precision': [0.6666666666666666, 0.6589147286821705, 0.6821705426356589, 0.7596899224806202, 0.6171875], 'avgPrecision': 0.6769258720930232, 'recall': [0.6666666666666666, 0.6589147286821705, 0.6821705426356589, 0.7596899224806202, 0.6171875], 'avgRecall': 0.6769258720930232, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.689922480620155, 0.813953488372093, 0.7751937984496124, 0.7364341085271318, 0.7578125], 'avgAccuracy': 0.7546632751937985, 'f1': [0.6664986680106559, 0.7759761041177725, 0.7170196609321097, 0.6813676633444076, 0.7175882043180621], 'avgF1': 0.7116900601446016, 'precision': [0.689922480620155, 0.813953488372093, 0.7751937984496124, 0.7364341085271318, 0.7578125], 'avgPrecision': 0.7546632751937985, 'recall': [0.689922480620155, 0.813953488372093, 0.7751937984496124, 0.7364341085271318, 0.7578125], 'avgRecall': 0.7546632751937985, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 50, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6666666666666666, 0.7829457364341085, 0.7441860465116279, 0.6744186046511628, 0.7421875], 'avgAccuracy': 0.7220809108527132, 'f1': [0.6392123153864188, 0.762015503875969, 0.7166880456627216, 0.6528775050905584, 0.717503586800574], 'avgF1': 0.6976593913632484, 'precision': [0.6666666666666666, 0.7829457364341085, 0.7441860465116279, 0.6744186046511628, 0.7421875], 'avgPrecision': 0.7220809108527132, 'recall': [0.6666666666666666, 0.7829457364341085, 0.7441860465116279, 0.6744186046511628, 0.7421875], 'avgRecall': 0.7220809108527132, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7608648255813953, 'f1': [0.6696954850957637, 0.7501835985312117, 0.7330833496189173, 0.6606878200386334, 0.7175882043180621], 'avgF1': 0.7062476915205177, 'precision': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7608648255813953, 'recall': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7608648255813953, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7608648255813953, 'f1': [0.6696954850957637, 0.7501835985312117, 0.7330833496189173, 0.6606878200386334, 0.7175882043180621], 'avgF1': 0.7062476915205177, 'precision': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7608648255813953, 'recall': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7608648255813953, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.745373  0.709940   0.745373  0.745373   
1  0.754675  0.715743   0.754675  0.754675   
2  0.756214  0.696448   0.756214  0.756214   
3  0.676926  0.694259   0.676926  0.676926   
4  0.754663  0.711690   0.754663  0.754663   
5  0.722081  0.697659   0.722081  0.722081   
6  0.754675  0.678040   0.754675  0.754675   
7  0.760865  0.706248   0.760865  0.760865   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'identity', 'alpha': 0.0001, 'b...  

now = datetime.datetime.now()
print ("Current date and time : ")
print (now.strftime("%Y-%m-%d %H:%M:%S"))

Current date and time : 
2021-06-05 11:25:12

# MSMOTE Dataset
X3 = pd.concat([X_msm, X_test_ord]) #.to_numpy()
y3 = pd.concat([y_msm, y_test_ord]).to_numpy()
#data = (X, y, n_folds)

print('********************************************')
print('Starting MSMOTE data set....')
print('********************************************')

for i in range(l ,6 , -1):
    col = []
    col = df[:i]
    nX3 = X3.loc[:, col]
    nX3 = nX3.to_numpy()
    data3 = (nX3, y3, n_folds)
    hyper_search(modelDictionary, modelParamsDictionary, data3, col)

********************************************
Starting MSMOTE data set....
********************************************

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgAccuracy': 0.9883794793088142, 'f1': [0.9743678853272765, 0.995916780089442, 0.9961302741477175, 1.0, 0.9793228295369784], 'avgF1': 0.9891475538202829, 'precision': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgPrecision': 0.9883794793088142, 'recall': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgRecall': 0.9883794793088142, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.9686289697908598, 0.9941905499612703, 0.9969016266460109, 0.9965143299767621, 0.9728787291747385], 'avgAccuracy': 0.9858228411099283, 'f1': [0.9676739206610505, 0.9970868129733929, 0.9969026764273867, 0.9982541222114452, 0.9758846916161877], 'avgF1': 0.9871604447778926, 'precision': [0.9686289697908598, 0.9941905499612703, 0.9969016266460109, 0.9965143299767621, 0.9728787291747385], 'avgPrecision': 0.9858228411099283, 'recall': [0.9686289697908598, 0.9941905499612703, 0.9969016266460109, 0.9965143299767621, 0.9728787291747385], 'avgRecall': 0.9858228411099283, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7405112316034083, 0.6994577846630519, 0.7854376452362509, 0.6646010844306739, 0.6594343277799303], 'avgAccuracy': 0.7098884147426631, 'f1': [0.777423060191904, 0.8231540565177757, 0.7867707062024818, 0.798510935318753, 0.7804853075974088], 'avgF1': 0.7932688131656647, 'precision': [0.7405112316034083, 0.6994577846630519, 0.7854376452362509, 0.6646010844306739, 0.6594343277799303], 'avgPrecision': 0.7098884147426631, 'recall': [0.7405112316034083, 0.6994577846630519, 0.7854376452362509, 0.6646010844306739, 0.6594343277799303], 'avgRecall': 0.7098884147426631, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 1000, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'lbfgs', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgAccuracy': 0.5707191713501903, 'f1': [0.25640924396388326, 0.23271731690622857, 0.3812585496570828, 1.0, 0.9790648204787236], 'avgF1': 0.5698899862011836, 'precision': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgPrecision': 0.5707191713501903, 'recall': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgRecall': 0.5707191713501903, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.84856700232378, 0.82571649883811, 0.8733539891556933, 0.7827265685515105, 0.7861294072065091], 'avgAccuracy': 0.8232986932151206, 'f1': [0.8633451762715798, 0.9045396690708528, 0.8738148077694966, 0.8781229632848142, 0.8663113674226026], 'avgF1': 0.8772267967638692, 'precision': [0.84856700232378, 0.82571649883811, 0.8733539891556933, 0.7827265685515105, 0.7861294072065091], 'avgPrecision': 0.8232986932151206, 'recall': [0.84856700232378, 0.82571649883811, 0.8733539891556933, 0.7827265685515105, 0.7861294072065091], 'avgRecall': 0.8232986932151206, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.9697908597986057, 0.9930286599535244, 0.9938032532920217, 0.9980635166537568, 0.9748159628051143], 'avgAccuracy': 0.9859004505006046, 'f1': [0.9691002688487015, 0.9965021375825883, 0.9938094503299437, 0.9990308199263424, 0.9771374854420583], 'avgF1': 0.9871160324259268, 'precision': [0.9697908597986057, 0.9930286599535244, 0.9938032532920217, 0.9980635166537568, 0.9748159628051143], 'avgPrecision': 0.9859004505006046, 'recall': [0.9697908597986057, 0.9930286599535244, 0.9938032532920217, 0.9980635166537568, 0.9748159628051143], 'avgRecall': 0.9859004505006046, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7447714949651433, 0.7498063516653757, 0.8024786986831913, 0.6413632842757552, 0.644711352189074], 'avgAccuracy': 0.7166262363557079, 'f1': [0.7800883034515573, 0.8570163789287295, 0.8019796875306643, 0.781500707881076, 0.769455076002716], 'avgF1': 0.7980080307589487, 'precision': [0.7447714949651433, 0.7498063516653757, 0.8024786986831913, 0.6413632842757552, 0.644711352189074], 'avgPrecision': 0.7166262363557079, 'recall': [0.7447714949651433, 0.7498063516653757, 0.8024786986831913, 0.6413632842757552, 0.644711352189074], 'avgRecall': 0.7166262363557079, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.9298993028659953, 0.9450038729666925, 0.9384198295894656, 0.8927188226181255, 0.8725300271212708], 'avgAccuracy': 0.9157143710323099, 'f1': [0.9305101722946922, 0.9717244125846276, 0.9382817272666095, 0.9433190096173522, 0.9184272413709469], 'avgF1': 0.9404525126268457, 'precision': [0.9298993028659953, 0.9450038729666925, 0.9384198295894656, 0.8927188226181255, 0.8725300271212708], 'avgPrecision': 0.9157143710323099, 'recall': [0.9298993028659953, 0.9450038729666925, 0.9384198295894656, 0.8927188226181255, 0.8725300271212708], 'avgRecall': 0.9157143710323099, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgAccuracy': 0.9883794793088142, 'f1': [0.9743678853272765, 0.995916780089442, 0.9961302741477175, 1.0, 0.9793228295369784], 'avgF1': 0.9891475538202829, 'precision': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgPrecision': 0.9883794793088142, 'recall': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgRecall': 0.9883794793088142, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.988379  0.989148   0.988379  0.988379   
1  0.985823  0.987160   0.985823  0.985823   
2  0.709888  0.793269   0.709888  0.709888   
3  0.570719  0.569890   0.570719  0.570719   
4  0.823299  0.877227   0.823299  0.823299   
5  0.985900  0.987116   0.985900  0.985900   
6  0.716626  0.798008   0.716626  0.716626   
7  0.915714  0.940453   0.915714  0.915714   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgAccuracy': 0.9883020499863299, 'f1': [0.9731674659131014, 0.9961119751166407, 0.9961302741477175, 1.0, 0.9798216331902337], 'avgF1': 0.9890462696735387, 'precision': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgPrecision': 0.9883020499863299, 'recall': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgRecall': 0.9883020499863299, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgAccuracy': 0.9860551891001123, 'f1': [0.9689345541874661, 0.9970868129733929, 0.9969026764273867, 0.9984484096198604, 0.9758248309524068], 'avgF1': 0.9874394568321025, 'precision': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgPrecision': 0.9860551891001123, 'recall': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgRecall': 0.9860551891001123, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7393493415956622, 0.6994577846630519, 0.7815646785437645, 0.6646010844306739, 0.6551724137931034], 'avgAccuracy': 0.7080290606052512, 'f1': [0.7764548243144944, 0.8231540565177757, 0.7829940556967838, 0.798510935318753, 0.7773747131425005], 'avgF1': 0.7916977169980615, 'precision': [0.7393493415956622, 0.6994577846630519, 0.7815646785437645, 0.6646010844306739, 0.6551724137931034], 'avgPrecision': 0.7080290606052512, 'recall': [0.7393493415956622, 0.6994577846630519, 0.7815646785437645, 0.6646010844306739, 0.6551724137931034], 'avgRecall': 0.7080290606052512, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'lbfgs', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgAccuracy': 0.5707191713501903, 'f1': [0.25640924396388326, 0.23271731690622857, 0.3812585496570828, 1.0, 0.9790648204787236], 'avgF1': 0.5698899862011836, 'precision': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgPrecision': 0.5707191713501903, 'recall': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgRecall': 0.5707191713501903, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.8489542989930287, 0.8187451587916343, 0.879163439194423, 0.7920216886134779, 0.7841921735761332], 'avgAccuracy': 0.8246153518337395, 'f1': [0.8637356720609862, 0.9003407155025552, 0.8795433200600168, 0.8839420791009294, 0.8650952794461256], 'avgF1': 0.8785314132341226, 'precision': [0.8489542989930287, 0.8187451587916343, 0.879163439194423, 0.7920216886134779, 0.7841921735761332], 'avgPrecision': 0.8246153518337395, 'recall': [0.8489542989930287, 0.8187451587916343, 0.879163439194423, 0.7920216886134779, 0.7841921735761332], 'avgRecall': 0.8246153518337395, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.9732765298218435, 0.9930286599535244, 0.9941905499612703, 0.9988381099922541, 0.9728787291747385], 'avgAccuracy': 0.9864425157807262, 'f1': [0.9727905244243396, 0.9965021375825883, 0.9941930054144381, 0.9994187173028483, 0.9760735647130044], 'avgF1': 0.9877955898874438, 'precision': [0.9732765298218435, 0.9930286599535244, 0.9941905499612703, 0.9988381099922541, 0.9728787291747385], 'avgPrecision': 0.9864425157807262, 'recall': [0.9732765298218435, 0.9930286599535244, 0.9941905499612703, 0.9988381099922541, 0.9728787291747385], 'avgRecall': 0.9864425157807262, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7455460883036406, 0.737412858249419, 0.7986057319907048, 0.6409759876065065, 0.6439364587369236], 'avgAccuracy': 0.7132954249774389, 'f1': [0.7806913607465088, 0.8488631297369593, 0.798284941105791, 0.7812131224923295, 0.7688794517439788], 'avgF1': 0.7955864011651135, 'precision': [0.7455460883036406, 0.737412858249419, 0.7986057319907048, 0.6409759876065065, 0.6439364587369236], 'avgPrecision': 0.7132954249774389, 'recall': [0.7455460883036406, 0.737412858249419, 0.7986057319907048, 0.6409759876065065, 0.6439364587369236], 'avgRecall': 0.7132954249774389, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.9360960495739736, 0.947714949651433, 0.935708752904725, 0.8826491092176607, 0.8717551336691205], 'avgAccuracy': 0.9147847990033826, 'f1': [0.936057893349985, 0.9731556969576457, 0.9356754163792643, 0.9376671466776383, 0.9179313583397674], 'avgF1': 0.9400975023408601, 'precision': [0.9360960495739736, 0.947714949651433, 0.935708752904725, 0.8826491092176607, 0.8717551336691205], 'avgPrecision': 0.9147847990033826, 'recall': [0.9360960495739736, 0.947714949651433, 0.935708752904725, 0.8826491092176607, 0.8717551336691205], 'avgRecall': 0.9147847990033826, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgAccuracy': 0.9883020499863299, 'f1': [0.9731674659131014, 0.9961119751166407, 0.9961302741477175, 1.0, 0.9798216331902337], 'avgF1': 0.9890462696735387, 'precision': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgPrecision': 0.9883020499863299, 'recall': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgRecall': 0.9883020499863299, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.988302  0.989046   0.988302  0.988302   
1  0.986055  0.987439   0.986055  0.986055   
2  0.708029  0.791698   0.708029  0.708029   
3  0.570719  0.569890   0.570719  0.570719   
4  0.824615  0.878531   0.824615  0.824615   
5  0.986443  0.987796   0.986443  0.986443   
6  0.713295  0.795586   0.713295  0.713295   
7  0.914785  0.940098   0.914785  0.914785   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgAccuracy': 0.9882245906524801, 'f1': [0.9732022021645715, 0.995916780089442, 0.9961302741477175, 1.0, 0.9795870048608761], 'avgF1': 0.9889672522525215, 'precision': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgPrecision': 0.9882245906524801, 'recall': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgRecall': 0.9882245906524801, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgAccuracy': 0.9860551891001123, 'f1': [0.9689345541874661, 0.9970868129733929, 0.9969026764273867, 0.9984484096198604, 0.9758248309524068], 'avgF1': 0.9874394568321025, 'precision': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgPrecision': 0.9860551891001123, 'recall': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgRecall': 0.9860551891001123, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7408985282726569, 0.7006196746707978, 0.7827265685515105, 0.6653756777691712, 0.6563347539713289], 'avgAccuracy': 0.709191040647093, 'f1': [0.7776698727945794, 0.8239580961056706, 0.7841127237588575, 0.7990697674418605, 0.7782246345606274], 'avgF1': 0.7926070189323191, 'precision': [0.7408985282726569, 0.7006196746707978, 0.7827265685515105, 0.6653756777691712, 0.6563347539713289], 'avgPrecision': 0.709191040647093, 'recall': [0.7408985282726569, 0.7006196746707978, 0.7827265685515105, 0.6653756777691712, 0.6563347539713289], 'avgRecall': 0.709191040647093, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.8454686289697909, 0.8280402788536019, 0.879163439194423, 0.7877614252517429, 0.7807051530414568], 'avgAccuracy': 0.8242277850622031, 'f1': [0.8609623792963672, 0.9059322033898305, 0.8794362077842383, 0.8812824956672444, 0.8628947564914238], 'avgF1': 0.8781016085258209, 'precision': [0.8454686289697909, 0.8280402788536019, 0.879163439194423, 0.7877614252517429, 0.7807051530414568], 'avgPrecision': 0.8242277850622031, 'recall': [0.8454686289697909, 0.8280402788536019, 0.879163439194423, 0.7877614252517429, 0.7807051530414568], 'avgRecall': 0.8242277850622031, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.9732765298218435, 0.9918667699457785, 0.9938032532920217, 0.993415956622773, 0.9767531964354901], 'avgAccuracy': 0.9858231412235814, 'f1': [0.9728605242690611, 0.995916780089442, 0.9938084386363477, 0.9966971051097725, 0.9779936838309122], 'avgF1': 0.9874553063871071, 'precision': [0.9732765298218435, 0.9918667699457785, 0.9938032532920217, 0.993415956622773, 0.9767531964354901], 'avgPrecision': 0.9858231412235814, 'recall': [0.9732765298218435, 0.9918667699457785, 0.9938032532920217, 0.993415956622773, 0.9767531964354901], 'avgRecall': 0.9858231412235814, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7451587916343919, 0.7397366382649109, 0.7986057319907048, 0.6413632842757552, 0.6439364587369236], 'avgAccuracy': 0.7137601809805373, 'f1': [0.7803898504701119, 0.85040071237756, 0.798284941105791, 0.781500707881076, 0.7688794517439788], 'avgF1': 0.7958911327157036, 'precision': [0.7451587916343919, 0.7397366382649109, 0.7986057319907048, 0.6413632842757552, 0.6439364587369236], 'avgPrecision': 0.7137601809805373, 'recall': [0.7451587916343919, 0.7397366382649109, 0.7986057319907048, 0.6413632842757552, 0.6439364587369236], 'avgRecall': 0.7137601809805373, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.9213787761425252, 0.947714949651433, 0.941130906274206, 0.8993028659953525, 0.8857032158078264], 'avgAccuracy': 0.9190461427742687, 'f1': [0.9230897102695093, 0.9731556969576457, 0.9409482185752528, 0.9469820554649266, 0.9260389794402553], 'avgF1': 0.9420429321415179, 'precision': [0.9213787761425252, 0.947714949651433, 0.941130906274206, 0.8993028659953525, 0.8857032158078264], 'avgPrecision': 0.9190461427742687, 'recall': [0.9213787761425252, 0.947714949651433, 0.941130906274206, 0.8993028659953525, 0.8857032158078264], 'avgRecall': 0.9190461427742687, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgAccuracy': 0.9882245906524801, 'f1': [0.9732022021645715, 0.995916780089442, 0.9961302741477175, 1.0, 0.9795870048608761], 'avgF1': 0.9889672522525215, 'precision': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgPrecision': 0.9882245906524801, 'recall': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgRecall': 0.9882245906524801, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.988225  0.988967   0.988225  0.988225   
1  0.986055  0.987439   0.986055  0.986055   
2  0.709191  0.792607   0.709191  0.709191   
3  0.562276  0.555955   0.562276  0.562276   
4  0.824228  0.878102   0.824228  0.824228   
5  0.985823  0.987455   0.985823  0.985823   
6  0.713760  0.795891   0.713760  0.713760   
7  0.919046  0.942043   0.919046  0.919046   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgAccuracy': 0.9883795393315449, 'f1': [0.9727905244243396, 0.9961119751166407, 0.9965169604138426, 1.0, 0.9798527702440915], 'avgF1': 0.9890544460397829, 'precision': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgPrecision': 0.9883795393315449, 'recall': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgRecall': 0.9883795393315449, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9736536226268888], 'avgAccuracy': 0.9862876571357573, 'f1': [0.9689345541874661, 0.9970868129733929, 0.9969026764273867, 0.9984484096198604, 0.9765737004271536], 'avgF1': 0.987589230727052, 'precision': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9736536226268888], 'avgPrecision': 0.9862876571357573, 'recall': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9736536226268888], 'avgRecall': 0.9862876571357573, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7443841982958946, 0.7029434546862897, 0.7862122385747483, 0.6618900077459334, 0.6648585819449826], 'avgAccuracy': 0.7120576962495697, 'f1': [0.7806325273130154, 0.8255628837843983, 0.7875879074837805, 0.7965509205313449, 0.7843592268776751], 'avgF1': 0.7949386931980429, 'precision': [0.7443841982958946, 0.7029434546862897, 0.7862122385747483, 0.6618900077459334, 0.6648585819449826], 'avgPrecision': 0.7120576962495697, 'recall': [0.7443841982958946, 0.7029434546862897, 0.7862122385747483, 0.6618900077459334, 0.6648585819449826], 'avgRecall': 0.7120576962495697, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.8272656855151046, 0.8121611154144074, 0.8826491092176607, 0.7757552285050349, 0.7826423866718326], 'avgAccuracy': 0.8160947050648081, 'f1': [0.8463246441406662, 0.8963453729429365, 0.8828871178796518, 0.8737186477644493, 0.8641182709362619], 'avgF1': 0.8726788107327932, 'precision': [0.8272656855151046, 0.8121611154144074, 0.8826491092176607, 0.7757552285050349, 0.7826423866718326], 'avgPrecision': 0.8160947050648081, 'recall': [0.8272656855151046, 0.8121611154144074, 0.8826491092176607, 0.7757552285050349, 0.7826423866718326], 'avgRecall': 0.8160947050648081, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.9709527498063517, 0.9926413632842758, 0.9953524399690162, 0.9980635166537568, 0.9728787291747385], 'avgAccuracy': 0.9859777597776278, 'f1': [0.9704626603534707, 0.9963070942662778, 0.9953555638756445, 0.9990308199263424, 0.9758846916161877], 'avgF1': 0.9874081660075846, 'precision': [0.9709527498063517, 0.9926413632842758, 0.9953524399690162, 0.9980635166537568, 0.9728787291747385], 'avgPrecision': 0.9859777597776278, 'recall': [0.9709527498063517, 0.9926413632842758, 0.9953524399690162, 0.9980635166537568, 0.9728787291747385], 'avgRecall': 0.9859777597776278, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7443841982958946, 0.7378001549186677, 0.7955073586367157, 0.6432997676219985, 0.6512979465323518], 'avgAccuracy': 0.7144578852011256, 'f1': [0.7797223424168295, 0.8491196790728773, 0.7954013243870571, 0.7829366014612302, 0.774395356274719], 'avgF1': 0.7963150607225427, 'precision': [0.7443841982958946, 0.7378001549186677, 0.7955073586367157, 0.6432997676219985, 0.6512979465323518], 'avgPrecision': 0.7144578852011256, 'recall': [0.7443841982958946, 0.7378001549186677, 0.7955073586367157, 0.6432997676219985, 0.6512979465323518], 'avgRecall': 0.7144578852011256, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.9186676994577847, 0.9473276529821844, 0.942292796281952, 0.8923315259488769, 0.8860906625339016], 'avgAccuracy': 0.9173420674409399, 'f1': [0.9210585051803777, 0.9729514717581542, 0.9421193137385487, 0.9431027425296765, 0.9261480658251595], 'avgF1': 0.9410760198063833, 'precision': [0.9186676994577847, 0.9473276529821844, 0.942292796281952, 0.8923315259488769, 0.8860906625339016], 'avgPrecision': 0.9173420674409399, 'recall': [0.9186676994577847, 0.9473276529821844, 0.942292796281952, 0.8923315259488769, 0.8860906625339016], 'avgRecall': 0.9173420674409399, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgAccuracy': 0.9883795393315449, 'f1': [0.9727905244243396, 0.9961119751166407, 0.9965169604138426, 1.0, 0.9798527702440915], 'avgF1': 0.9890544460397829, 'precision': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgPrecision': 0.9883795393315449, 'recall': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgRecall': 0.9883795393315449, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.988380  0.989054   0.988380  0.988380   
1  0.986288  0.987589   0.986288  0.986288   
2  0.712058  0.794939   0.712058  0.712058   
3  0.562276  0.555955   0.562276  0.562276   
4  0.816095  0.872679   0.816095  0.816095   
5  0.985978  0.987408   0.985978  0.985978   
6  0.714458  0.796315   0.714458  0.714458   
7  0.917342  0.941076   0.917342  0.917342   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgAccuracy': 0.9883795393315449, 'f1': [0.9727551528306728, 0.9961119751166407, 0.9965169604138426, 1.0, 0.9798527702440915], 'avgF1': 0.9890473717210495, 'precision': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgPrecision': 0.9883795393315449, 'recall': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgRecall': 0.9883795393315449, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9972889233152595, 0.9736536226268888], 'avgAccuracy': 0.9865200351373065, 'f1': [0.9689345541874661, 0.9972815533980581, 0.9972896136271163, 0.9986426216792708, 0.9765737004271536], 'avgF1': 0.987744408663813, 'precision': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9972889233152595, 0.9736536226268888], 'avgPrecision': 0.9865200351373065, 'recall': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9972889233152595, 0.9736536226268888], 'avgRecall': 0.9865200351373065, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7513555383423702, 0.703718048024787, 0.790859798605732, 0.6595662277304415, 0.6536226268888028], 'avgAccuracy': 0.7118244479184267, 'f1': [0.786274850083763, 0.8260968401909524, 0.7921825020771343, 0.7948658109684947, 0.776172039127646], 'avgF1': 0.795118408489598, 'precision': [0.7513555383423702, 0.703718048024787, 0.790859798605732, 0.6595662277304415, 0.6536226268888028], 'avgPrecision': 0.7118244479184267, 'recall': [0.7513555383423702, 0.703718048024787, 0.790859798605732, 0.6595662277304415, 0.6536226268888028], 'avgRecall': 0.7118244479184267, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.8264910921766073, 0.7877614252517429, 0.8683191324554609, 0.7602633617350891, 0.774118558698179], 'avgAccuracy': 0.8033907140634159, 'f1': [0.8461028615839487, 0.8812824956672444, 0.868733105193608, 0.8638063806380638, 0.8587159127126046], 'avgF1': 0.8637281511590938, 'precision': [0.8264910921766073, 0.7877614252517429, 0.8683191324554609, 0.7602633617350891, 0.774118558698179], 'avgPrecision': 0.8033907140634159, 'recall': [0.8264910921766073, 0.7877614252517429, 0.8683191324554609, 0.7602633617350891, 0.774118558698179], 'avgRecall': 0.8033907140634159, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.9740511231603408, 0.9903175832687839, 0.9953524399690162, 0.9988381099922541, 0.9744285160790391], 'avgAccuracy': 0.9865975544938869, 'f1': [0.9735792048758081, 0.9951352403191283, 0.9953563289772609, 0.9994187173028483, 0.9757930522140035], 'avgF1': 0.9878565087378098, 'precision': [0.9740511231603408, 0.9903175832687839, 0.9953524399690162, 0.9988381099922541, 0.9744285160790391], 'avgPrecision': 0.9865975544938869, 'recall': [0.9740511231603408, 0.9903175832687839, 0.9953524399690162, 0.9988381099922541, 0.9744285160790391], 'avgRecall': 0.9865975544938869, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7536793183578622, 0.750580945003873, 0.8067389620449265, 0.6367157242447715, 0.6443239054629989], 'avgAccuracy': 0.7184077710228864, 'f1': [0.7870151680116803, 0.8575221238938054, 0.806195271360556, 0.7780407004259348, 0.7692399404136899], 'avgF1': 0.7996026408211333, 'precision': [0.7536793183578622, 0.750580945003873, 0.8067389620449265, 0.6367157242447715, 0.6443239054629989], 'avgPrecision': 0.7184077710228864, 'recall': [0.7536793183578622, 0.750580945003873, 0.8067389620449265, 0.6367157242447715, 0.6443239054629989], 'avgRecall': 0.7184077710228864, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.9186676994577847, 0.9457784663051898, 0.9391944229279628, 0.8818745158791634, 0.8655559860519179], 'avgAccuracy': 0.9102142181244037, 'f1': [0.9209775162588809, 0.9721337579617836, 0.93897590349354, 0.9372298826919118, 0.9143682896876353], 'avgF1': 0.9367370700187503, 'precision': [0.9186676994577847, 0.9457784663051898, 0.9391944229279628, 0.8818745158791634, 0.8655559860519179], 'avgPrecision': 0.9102142181244037, 'recall': [0.9186676994577847, 0.9457784663051898, 0.9391944229279628, 0.8818745158791634, 0.8655559860519179], 'avgRecall': 0.9102142181244037, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgAccuracy': 0.9883795393315449, 'f1': [0.9727551528306728, 0.9961119751166407, 0.9965169604138426, 1.0, 0.9798527702440915], 'avgF1': 0.9890473717210495, 'precision': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgPrecision': 0.9883795393315449, 'recall': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgRecall': 0.9883795393315449, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.988380  0.989047   0.988380  0.988380   
1  0.986520  0.987744   0.986520  0.986520   
2  0.711824  0.795118   0.711824  0.711824   
3  0.562276  0.555955   0.562276  0.562276   
4  0.803391  0.863728   0.803391  0.803391   
5  0.986598  0.987857   0.986598  0.986598   
6  0.718408  0.799603   0.718408  0.718408   
7  0.910214  0.936737   0.910214  0.910214   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgAccuracy': 0.9879147233057158, 'f1': [0.9723782737340749, 0.9957215091404122, 0.9965169604138426, 0.999806314158435, 0.9793228295369784], 'avgF1': 0.9887491773967486, 'precision': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgPrecision': 0.9879147233057158, 'recall': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgRecall': 0.9879147233057158, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.974041069352964], 'avgAccuracy': 0.9863651464809723, 'f1': [0.9689345541874661, 0.9972815533980581, 0.9972896136271163, 0.9980597594101667, 0.9766334901142151], 'avgF1': 0.9876397941474044, 'precision': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.974041069352964], 'avgPrecision': 0.9863651464809723, 'recall': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.974041069352964], 'avgRecall': 0.9863651464809723, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7532920216886135, 0.7114639814097599, 0.7900852052672347, 0.6638264910921766, 0.6621464548624564], 'avgAccuracy': 0.7161628308640482, 'f1': [0.7877340247253514, 0.8314098212265219, 0.7914359526380598, 0.797951582867784, 0.7824565269482253], 'avgF1': 0.7981975816811885, 'precision': [0.7532920216886135, 0.7114639814097599, 0.7900852052672347, 0.6638264910921766, 0.6621464548624564], 'avgPrecision': 0.7161628308640482, 'recall': [0.7532920216886135, 0.7114639814097599, 0.7900852052672347, 0.6638264910921766, 0.6621464548624564], 'avgRecall': 0.7161628308640482, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.8164213787761425, 0.78001549186677, 0.8675445391169636, 0.790859798605732, 0.7644323905462999], 'avgAccuracy': 0.8038547197823815, 'f1': [0.8372517832882455, 0.8764142732811141, 0.8679986680680337, 0.8832179930795847, 0.8525553749749708], 'avgF1': 0.8634876185383897, 'precision': [0.8164213787761425, 0.78001549186677, 0.8675445391169636, 0.790859798605732, 0.7644323905462999], 'avgPrecision': 0.8038547197823815, 'recall': [0.8164213787761425, 0.78001549186677, 0.8675445391169636, 0.790859798605732, 0.7644323905462999], 'avgRecall': 0.8038547197823815, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.969403563129357, 0.9910921766072812, 0.9957397366382649, 0.9965143299767621, 0.9755908562572646], 'avgAccuracy': 0.985668132521786, 'f1': [0.9688066242554079, 0.9955261622252479, 0.99574082141404, 0.9982541222114452, 0.9774420173402057], 'avgF1': 0.9871539494892694, 'precision': [0.969403563129357, 0.9910921766072812, 0.9957397366382649, 0.9965143299767621, 0.9755908562572646], 'avgPrecision': 0.985668132521786, 'recall': [0.969403563129357, 0.9910921766072812, 0.9957397366382649, 0.9965143299767621, 0.9755908562572646], 'avgRecall': 0.985668132521786, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7532920216886135, 0.7517428350116189, 0.7970565453137103, 0.62858249419055, 0.6369624176675707], 'avgAccuracy': 0.7135272627744127, 'f1': [0.7867820788492016, 0.8582799027194339, 0.7971253059938356, 0.7719381688466113, 0.7638266856189538], 'avgF1': 0.7955904284056072, 'precision': [0.7532920216886135, 0.7517428350116189, 0.7970565453137103, 0.62858249419055, 0.6369624176675707], 'avgPrecision': 0.7135272627744127, 'recall': [0.7532920216886135, 0.7517428350116189, 0.7970565453137103, 0.62858249419055, 0.6369624176675707], 'avgRecall': 0.7135272627744127, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.9182804027885361, 0.947714949651433, 0.9403563129357088, 0.831138652207591, 0.8833785354513755], 'avgAccuracy': 0.9041737706069288, 'f1': [0.920560326588896, 0.9731556969576457, 0.9402613094813305, 0.907783417935702, 0.924646238552518], 'avgF1': 0.9332813979032184, 'precision': [0.9182804027885361, 0.947714949651433, 0.9403563129357088, 0.831138652207591, 0.8833785354513755], 'avgPrecision': 0.9041737706069288, 'recall': [0.9182804027885361, 0.947714949651433, 0.9403563129357088, 0.831138652207591, 0.8833785354513755], 'avgRecall': 0.9041737706069288, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgAccuracy': 0.9879147233057158, 'f1': [0.9723782737340749, 0.9957215091404122, 0.9965169604138426, 0.999806314158435, 0.9793228295369784], 'avgF1': 0.9887491773967486, 'precision': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgPrecision': 0.9879147233057158, 'recall': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgRecall': 0.9879147233057158, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.987915  0.988749   0.987915  0.987915   
1  0.986365  0.987640   0.986365  0.986365   
2  0.716163  0.798198   0.716163  0.716163   
3  0.562276  0.555955   0.562276  0.562276   
4  0.803855  0.863488   0.803855  0.803855   
5  0.985668  0.987154   0.985668  0.985668   
6  0.713527  0.795590   0.713527  0.713527   
7  0.904174  0.933281   0.904174  0.904174   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgAccuracy': 0.9879148133398118, 'f1': [0.9715890815550484, 0.9955261622252479, 0.9965169604138426, 0.999806314158435, 0.98012018747861], 'avgF1': 0.9887117411662368, 'precision': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgPrecision': 0.9879148133398118, 'recall': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgRecall': 0.9879148133398118, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.9736536226268888], 'avgAccuracy': 0.9862876571357573, 'f1': [0.9689345541874661, 0.9972815533980581, 0.9972896136271163, 0.9980597594101667, 0.9763829613145928], 'avgF1': 0.98758968838748, 'precision': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.9736536226268888], 'avgPrecision': 0.9862876571357573, 'recall': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.9736536226268888], 'avgRecall': 0.9862876571357573, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7606506584043378, 0.7223082881487219, 0.7978311386522076, 0.6642137877614253, 0.6598217745060054], 'avgAccuracy': 0.7209651294945396, 'f1': [0.7933676263388896, 0.8387677085675735, 0.7989463800654896, 0.7982313241796601, 0.7807027206038801], 'avgF1': 0.8020031519510986, 'precision': [0.7606506584043378, 0.7223082881487219, 0.7978311386522076, 0.6642137877614253, 0.6598217745060054], 'avgPrecision': 0.7209651294945396, 'recall': [0.7606506584043378, 0.7223082881487219, 0.7978311386522076, 0.6642137877614253, 0.6598217745060054], 'avgRecall': 0.7209651294945396, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.8121611154144074, 0.7966692486444616, 0.8733539891556933, 0.784275755228505, 0.7679194110809764], 'avgAccuracy': 0.8068759039048088, 'f1': [0.834074527907235, 0.8868290579866351, 0.8736302403662103, 0.8790970262643802, 0.8547786046065992], 'avgF1': 0.865681891426212, 'precision': [0.8121611154144074, 0.7966692486444616, 0.8733539891556933, 0.784275755228505, 0.7679194110809764], 'avgPrecision': 0.8068759039048088, 'recall': [0.8121611154144074, 0.7966692486444616, 0.8733539891556933, 0.784275755228505, 0.7679194110809764], 'avgRecall': 0.8068759039048088, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.9728892331525949, 0.9926413632842758, 0.9953524399690162, 0.9965143299767621, 0.9748159628051143], 'avgAccuracy': 0.9864426658375527, 'f1': [0.9723059961548532, 0.9963070942662778, 0.9953563289772609, 0.9982541222114452, 0.9762780159978284], 'avgF1': 0.9877003115215331, 'precision': [0.9728892331525949, 0.9926413632842758, 0.9953524399690162, 0.9965143299767621, 0.9748159628051143], 'avgPrecision': 0.9864426658375527, 'recall': [0.9728892331525949, 0.9926413632842758, 0.9953524399690162, 0.9965143299767621, 0.9748159628051143], 'avgRecall': 0.9864426658375527, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7552285050348567, 0.7575522850503486, 0.7997676219984509, 0.62858249419055, 0.6369624176675707], 'avgAccuracy': 0.7156186647883553, 'f1': [0.7882181347268206, 0.8620537681798148, 0.7995753784801307, 0.7719381688466113, 0.7638266856189538], 'avgF1': 0.7971224271704662, 'precision': [0.7552285050348567, 0.7575522850503486, 0.7997676219984509, 0.62858249419055, 0.6369624176675707], 'avgPrecision': 0.7156186647883553, 'recall': [0.7552285050348567, 0.7575522850503486, 0.7997676219984509, 0.62858249419055, 0.6369624176675707], 'avgRecall': 0.7156186647883553, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.9264136328427576, 0.929124709527498, 0.9573973663826492, 0.8315259488768396, 0.8454087562960093], 'avgAccuracy': 0.8979740827851508, 'f1': [0.9275046500660639, 0.9632603894800242, 0.9570873638940116, 0.9080143793613872, 0.9025412197478779], 'avgF1': 0.9316816005098729, 'precision': [0.9264136328427576, 0.929124709527498, 0.9573973663826492, 0.8315259488768396, 0.8454087562960093], 'avgPrecision': 0.8979740827851508, 'recall': [0.9264136328427576, 0.929124709527498, 0.9573973663826492, 0.8315259488768396, 0.8454087562960093], 'avgRecall': 0.8979740827851508, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgAccuracy': 0.9879148133398118, 'f1': [0.9715890815550484, 0.9955261622252479, 0.9965169604138426, 0.999806314158435, 0.98012018747861], 'avgF1': 0.9887117411662368, 'precision': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgPrecision': 0.9879148133398118, 'recall': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgRecall': 0.9879148133398118, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.987915  0.988712   0.987915  0.987915   
1  0.986288  0.987590   0.986288  0.986288   
2  0.720965  0.802003   0.720965  0.720965   
3  0.562276  0.555955   0.562276  0.562276   
4  0.806876  0.865682   0.806876  0.806876   
5  0.986443  0.987700   0.986443  0.986443   
6  0.715619  0.797122   0.715619  0.715619   
7  0.897974  0.931682   0.897974  0.897974   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgAccuracy': 0.8853440998105983, 'f1': [0.9318672032153393, 0.984863377236092, 0.9239980821952671, 0.8927958833619212, 0.8701985112564117], 'avgF1': 0.9207446114530062, 'precision': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgPrecision': 0.8853440998105983, 'recall': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgRecall': 0.8853440998105983, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.9306738962044926, 0.9442292796281953, 0.9260263361735089, 0.814872192099148, 0.797752808988764], 'avgAccuracy': 0.8827109026188218, 'f1': [0.9292289271642805, 0.9713147410358566, 0.9245789359229387, 0.897994024754588, 0.8735873898087486], 'avgF1': 0.9193408037372824, 'precision': [0.9306738962044926, 0.9442292796281953, 0.9260263361735089, 0.814872192099148, 0.797752808988764], 'avgPrecision': 0.8827109026188218, 'recall': [0.9306738962044926, 0.9442292796281953, 0.9260263361735089, 0.814872192099148, 0.797752808988764], 'avgRecall': 0.8827109026188218, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7931835786212239, 0.6192873741285825, 0.8059643687064292, 0.6673121611154144, 0.6582719876017048], 'avgAccuracy': 0.7088038940346709, 'f1': [0.8170071032689387, 0.7648887825878976, 0.8057433323606248, 0.8004645760743322, 0.7795732053514963], 'avgF1': 0.793535399928658, 'precision': [0.7931835786212239, 0.6192873741285825, 0.8059643687064292, 0.6673121611154144, 0.6582719876017048], 'avgPrecision': 0.7088038940346709, 'recall': [0.7931835786212239, 0.6192873741285825, 0.8059643687064292, 0.6673121611154144, 0.6582719876017048], 'avgRecall': 0.7088038940346709, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.8032532920216886, 0.7831138652207591, 0.8195197521301317, 0.6785437645236251, 0.6780317706315382], 'avgAccuracy': 0.7524924889055485, 'f1': [0.8251407686907716, 0.8783666377063423, 0.8194261688719104, 0.8084910013844023, 0.7938195078211951], 'avgF1': 0.8250488168949244, 'precision': [0.8032532920216886, 0.7831138652207591, 0.8195197521301317, 0.6785437645236251, 0.6780317706315382], 'avgPrecision': 0.7524924889055485, 'recall': [0.8032532920216886, 0.7831138652207591, 0.8195197521301317, 0.6785437645236251, 0.6780317706315382], 'avgRecall': 0.7524924889055485, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.9306738962044926, 0.9686289697908598, 0.9244771494965144, 0.8044151820294345, 0.7900038744672607], 'avgAccuracy': 0.8836398143977124, 'f1': [0.9290421309803026, 0.9840645288215619, 0.9235778993761502, 0.8916076411247048, 0.8687425347188019], 'avgF1': 0.9194069470043043, 'precision': [0.9306738962044926, 0.9686289697908598, 0.9244771494965144, 0.8044151820294345, 0.7900038744672607], 'avgPrecision': 0.8836398143977124, 'recall': [0.9306738962044926, 0.9686289697908598, 0.9244771494965144, 0.8044151820294345, 0.7900038744672607], 'avgRecall': 0.8836398143977124, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.8109992254066615, 0.8024786986831913, 0.8171959721146398, 0.6332300542215337, 0.6338628438589694], 'avgAccuracy': 0.7395533588569991, 'f1': [0.8310493187351712, 0.8904168457241083, 0.815700526111898, 0.7754327721128764, 0.7613468292498494], 'avgF1': 0.8147892583867806, 'precision': [0.8109992254066615, 0.8024786986831913, 0.8171959721146398, 0.6332300542215337, 0.6338628438589694], 'avgPrecision': 0.7395533588569991, 'recall': [0.8109992254066615, 0.8024786986831913, 0.8171959721146398, 0.6332300542215337, 0.6338628438589694], 'avgRecall': 0.7395533588569991, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.9287374128582494, 0.965143299767622, 0.919442292796282, 0.8067389620449265, 0.7942657884540876], 'avgAccuracy': 0.8828655511842335, 'f1': [0.9275816441579903, 0.9822625147812375, 0.918431958676894, 0.8930332261521973, 0.8714083132864341], 'avgF1': 0.9185435314109506, 'precision': [0.9287374128582494, 0.965143299767622, 0.919442292796282, 0.8067389620449265, 0.7942657884540876], 'avgPrecision': 0.8828655511842335, 'recall': [0.9287374128582494, 0.965143299767622, 0.919442292796282, 0.8067389620449265, 0.7942657884540876], 'avgRecall': 0.8828655511842335, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgAccuracy': 0.8853440998105983, 'f1': [0.9318672032153393, 0.984863377236092, 0.9239980821952671, 0.8927958833619212, 0.8701985112564117], 'avgF1': 0.9207446114530062, 'precision': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgPrecision': 0.8853440998105983, 'recall': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgRecall': 0.8853440998105983, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.885344  0.920745   0.885344  0.885344   
1  0.882711  0.919341   0.882711  0.882711   
2  0.708804  0.793535   0.708804  0.708804   
3  0.562276  0.555955   0.562276  0.562276   
4  0.752492  0.825049   0.752492  0.752492   
5  0.883640  0.919407   0.883640  0.883640   
6  0.739553  0.814789   0.739553  0.739553   
7  0.882866  0.918544   0.882866  0.882866   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8059643687064292, 0.7938783417280124], 'avgAccuracy': 0.8855765978576087, 'f1': [0.9320414800091605, 0.984863377236092, 0.9239980821952671, 0.8925584387733219, 0.8711665843469139], 'avgF1': 0.9209255925121511, 'precision': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8059643687064292, 0.7938783417280124], 'avgPrecision': 0.8855765978576087, 'recall': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8059643687064292, 0.7938783417280124], 'avgRecall': 0.8855765978576087, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgAccuracy': 0.8875901503899527, 'f1': [0.9281835117085948, 0.9925868123293016, 0.9175891771378678, 0.8982291444420738, 0.8680051095162222], 'avgF1': 0.9209187510268121, 'precision': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgPrecision': 0.8875901503899527, 'recall': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgRecall': 0.8875901503899527, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7885360185902401, 0.6014717273431448, 0.80286599535244, 0.656855151045701, 0.651685393258427], 'avgAccuracy': 0.7002828571179905, 'f1': [0.8135087148490493, 0.751148730350665, 0.8027809827234254, 0.7928938756428238, 0.7745422804888014], 'avgF1': 0.786974916810953, 'precision': [0.7885360185902401, 0.6014717273431448, 0.80286599535244, 0.656855151045701, 0.651685393258427], 'avgPrecision': 0.7002828571179905, 'recall': [0.7885360185902401, 0.6014717273431448, 0.80286599535244, 0.656855151045701, 0.651685393258427], 'avgRecall': 0.7002828571179905, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.8032532920216886, 0.7831138652207591, 0.8226181254841208, 0.7122385747482571, 0.7047655947307245], 'avgAccuracy': 0.7651978904411101, 'f1': [0.8251407686907716, 0.8783666377063423, 0.822400087921541, 0.8319384754580411, 0.8125309123058684], 'avgF1': 0.8340753764165129, 'precision': [0.8032532920216886, 0.7831138652207591, 0.8226181254841208, 0.7122385747482571, 0.7047655947307245], 'avgPrecision': 0.7651978904411101, 'recall': [0.8032532920216886, 0.7831138652207591, 0.8226181254841208, 0.7122385747482571, 0.7047655947307245], 'avgRecall': 0.7651978904411101, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.9298993028659953, 0.9705654531371031, 0.923702556158017, 0.8040278853601859, 0.7892289810151104], 'avgAccuracy': 0.8834848357072823, 'f1': [0.9286244191421082, 0.9850628930817611, 0.9228132529623144, 0.8913696865607557, 0.8682488838367678], 'avgF1': 0.9192238271167414, 'precision': [0.9298993028659953, 0.9705654531371031, 0.923702556158017, 0.8040278853601859, 0.7892289810151104], 'avgPrecision': 0.8834848357072823, 'recall': [0.9298993028659953, 0.9705654531371031, 0.923702556158017, 0.8040278853601859, 0.7892289810151104], 'avgRecall': 0.8834848357072823, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7974438419829589, 0.7424477149496514, 0.8156467854376452, 0.639426800929512, 0.6268888027896165], 'avgAccuracy': 0.7243707892178768, 'f1': [0.8203832924383659, 0.8521893754167594, 0.8145075947224464, 0.7800614221592251, 0.7559959193065631], 'avgF1': 0.804627520808672, 'precision': [0.7974438419829589, 0.7424477149496514, 0.8156467854376452, 0.639426800929512, 0.6268888027896165], 'avgPrecision': 0.7243707892178768, 'recall': [0.7974438419829589, 0.7424477149496514, 0.8156467854376452, 0.639426800929512, 0.6268888027896165], 'avgRecall': 0.7243707892178768, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.9264136328427576, 0.9624322230828815, 0.9190549961270333, 0.7947327652982185, 0.7950406819062379], 'avgAccuracy': 0.8795348598514258, 'f1': [0.925692038022254, 0.9808565225971977, 0.9180707244508202, 0.8856279671989642, 0.8718899656420951], 'avgF1': 0.9164274435822662, 'precision': [0.9264136328427576, 0.9624322230828815, 0.9190549961270333, 0.7947327652982185, 0.7950406819062379], 'avgPrecision': 0.8795348598514258, 'recall': [0.9264136328427576, 0.9624322230828815, 0.9190549961270333, 0.7947327652982185, 0.7950406819062379], 'avgRecall': 0.8795348598514258, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgAccuracy': 0.8875901503899527, 'f1': [0.9281835117085948, 0.9925868123293016, 0.9175891771378678, 0.8982291444420738, 0.8680051095162222], 'avgF1': 0.9209187510268121, 'precision': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgPrecision': 0.8875901503899527, 'recall': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgRecall': 0.8875901503899527, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.885577  0.920926   0.885577  0.885577   
1  0.887590  0.920919   0.887590  0.887590   
2  0.700283  0.786975   0.700283  0.700283   
3  0.562276  0.555955   0.562276  0.562276   
4  0.765198  0.834075   0.765198  0.765198   
5  0.883485  0.919224   0.883485  0.883485   
6  0.724371  0.804628   0.724371  0.724371   
7  0.879535  0.916427   0.879535  0.879535   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgAccuracy': 0.8903808172154795, 'f1': [0.9315174243667953, 0.984863377236092, 0.9239980821952671, 0.8937446443873178, 0.885076746436222], 'avgF1': 0.9238400549243388, 'precision': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgPrecision': 0.8903808172154795, 'recall': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgRecall': 0.8903808172154795, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.9295120061967467, 0.9848954298993029, 0.9233152594887684, 0.8032532920216886, 0.7872917473847346], 'avgAccuracy': 0.8856535469982483, 'f1': [0.9282764822640005, 0.9923902439024389, 0.9224118228753246, 0.890893470790378, 0.8670290327476512], 'avgF1': 0.9202002105159587, 'precision': [0.9295120061967467, 0.9848954298993029, 0.9233152594887684, 0.8032532920216886, 0.7872917473847346], 'avgPrecision': 0.8856535469982483, 'recall': [0.9295120061967467, 0.9848954298993029, 0.9233152594887684, 0.8032532920216886, 0.7872917473847346], 'avgRecall': 0.8856535469982483, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6537567776917118, 0.6065065840433772, 0.8226181254841208, 0.6301316808675446, 0.6218519953506393], 'avgAccuracy': 0.6669730326874788, 'f1': [0.7078962045168463, 0.7550626808100289, 0.8201163419931231, 0.7731052506533619, 0.7521595579342258], 'avgF1': 0.7616680071815172, 'precision': [0.6537567776917118, 0.6065065840433772, 0.8226181254841208, 0.6301316808675446, 0.6218519953506393], 'avgPrecision': 0.6669730326874788, 'recall': [0.6537567776917118, 0.6065065840433772, 0.8226181254841208, 0.6301316808675446, 0.6218519953506393], 'avgRecall': 0.6669730326874788, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6440743609604958, 0.6177381874515879, 0.8315259488768396, 0.7122385747482571, 0.7047655947307245], 'avgAccuracy': 0.702068533353581, 'f1': [0.6997310918189729, 0.7637060090974384, 0.8306460431433276, 0.8319384754580411, 0.8125309123058684], 'avgF1': 0.7877105063647296, 'precision': [0.6440743609604958, 0.6177381874515879, 0.8315259488768396, 0.7122385747482571, 0.7047655947307245], 'avgPrecision': 0.702068533353581, 'recall': [0.6440743609604958, 0.6177381874515879, 0.8315259488768396, 0.7122385747482571, 0.7047655947307245], 'avgRecall': 0.702068533353581, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.9298993028659953, 0.9682416731216111, 0.923702556158017, 0.8059643687064292, 0.8159628051142968], 'avgAccuracy': 0.8887541411932699, 'f1': [0.9288080419231897, 0.9838646202282565, 0.9228132529623144, 0.8925584387733219, 0.8848593922885515], 'avgF1': 0.9225807492351268, 'precision': [0.9298993028659953, 0.9682416731216111, 0.923702556158017, 0.8059643687064292, 0.8159628051142968], 'avgPrecision': 0.8887541411932699, 'recall': [0.9298993028659953, 0.9682416731216111, 0.923702556158017, 0.8059643687064292, 0.8159628051142968], 'avgRecall': 0.8887541411932699, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.808288148721921, 0.6340046475600309, 0.8272656855151046, 0.6204492641363284, 0.6013173188686556], 'avgAccuracy': 0.6982650129604081, 'f1': [0.8284850975609559, 0.7760132732875089, 0.8242609930903515, 0.765774378585086, 0.7361743533334244], 'avgF1': 0.7861416191714653, 'precision': [0.808288148721921, 0.6340046475600309, 0.8272656855151046, 0.6204492641363284, 0.6013173188686556], 'avgPrecision': 0.6982650129604081, 'recall': [0.808288148721921, 0.6340046475600309, 0.8272656855151046, 0.6204492641363284, 0.6013173188686556], 'avgRecall': 0.6982650129604081, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.9268009295120062, 0.9604957397366383, 0.9186676994577847, 0.8237800154918667, 0.8066640836884929], 'avgAccuracy': 0.8872816935773578, 'f1': [0.9260369304242264, 0.9798498617147372, 0.9176683932444094, 0.9033765130600976, 0.8791246839616708], 'avgF1': 0.9212112764810283, 'precision': [0.9268009295120062, 0.9604957397366383, 0.9186676994577847, 0.8237800154918667, 0.8066640836884929], 'avgPrecision': 0.8872816935773578, 'recall': [0.9268009295120062, 0.9604957397366383, 0.9186676994577847, 0.8237800154918667, 0.8066640836884929], 'avgRecall': 0.8872816935773578, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgAccuracy': 0.8903808172154795, 'f1': [0.9315174243667953, 0.984863377236092, 0.9239980821952671, 0.8937446443873178, 0.885076746436222], 'avgF1': 0.9238400549243388, 'precision': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgPrecision': 0.8903808172154795, 'recall': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgRecall': 0.8903808172154795, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.890381  0.923840   0.890381  0.890381   
1  0.885654  0.920200   0.885654  0.885654   
2  0.666973  0.761668   0.666973  0.666973   
3  0.562276  0.555955   0.562276  0.562276   
4  0.702069  0.787711   0.702069  0.702069   
5  0.888754  0.922581   0.888754  0.888754   
6  0.698265  0.786142   0.698265  0.698265   
7  0.887282  0.921211   0.887282  0.887282   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgAccuracy': 0.8733372428138536, 'f1': [0.9134793606749531, 0.9749900754267568, 0.9083038949258901, 0.8946917808219178, 0.8648212048724403], 'avgF1': 0.9112572633443916, 'precision': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgPrecision': 0.8733372428138536, 'recall': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgRecall': 0.8733372428138536, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.9027885360185902, 0.9508133230054222, 0.9078233927188226, 0.8117738187451587, 0.77644323905463], 'avgAccuracy': 0.8699284619085248, 'f1': [0.9045965385958659, 0.9747865793130831, 0.9062460614636522, 0.8961094484822573, 0.8601426360762431], 'avgF1': 0.9083762527862203, 'precision': [0.9027885360185902, 0.9508133230054222, 0.9078233927188226, 0.8117738187451587, 0.77644323905463], 'avgPrecision': 0.8699284619085248, 'recall': [0.9027885360185902, 0.9508133230054222, 0.9078233927188226, 0.8117738187451587, 0.77644323905463], 'avgRecall': 0.8699284619085248, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.8036405886909372, 0.7486444616576298, 0.8164213787761425, 0.6150271107668474, 0.5966679581557536], 'avgAccuracy': 0.7160802996094621, 'f1': [0.8247083735709287, 0.8562569213732003, 0.8154433366621827, 0.7616306954436451, 0.732808466145676], 'avgF1': 0.7981695586391265, 'precision': [0.8036405886909372, 0.7486444616576298, 0.8164213787761425, 0.6150271107668474, 0.5966679581557536], 'avgPrecision': 0.7160802996094621, 'recall': [0.8036405886909372, 0.7486444616576298, 0.8164213787761425, 0.6150271107668474, 0.5966679581557536], 'avgRecall': 0.7160802996094621, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgAccuracy': 0.7614793622344782, 'f1': [0.8198155911067191, 0.8781229632848142, 0.8166686000561928, 0.8314098212265219, 0.8084146843926965], 'avgF1': 0.8308863320133889, 'precision': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgPrecision': 0.7614793622344782, 'recall': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgRecall': 0.7614793622344782, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.9120836560805577, 0.9500387296669248, 0.9082106893880713, 0.8067389620449265, 0.7799302595893065], 'avgAccuracy': 0.8714004593539574, 'f1': [0.9125480515766394, 0.9743793445878849, 0.9067042559189009, 0.8930332261521973, 0.8623710770429008], 'avgF1': 0.9098071910557046, 'precision': [0.9120836560805577, 0.9500387296669248, 0.9082106893880713, 0.8067389620449265, 0.7799302595893065], 'avgPrecision': 0.8714004593539574, 'recall': [0.9120836560805577, 0.9500387296669248, 0.9082106893880713, 0.8067389620449265, 0.7799302595893065], 'avgRecall': 0.8714004593539574, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7804027885360186, 0.761425251742835, 0.8160340821068939, 0.620836560805577, 0.642386671832623], 'avgAccuracy': 0.7242170710047895, 'f1': [0.8064685534997607, 0.8645558487247141, 0.8141613484696684, 0.7660692951015531, 0.7675787821565135], 'avgF1': 0.8037667655904419, 'precision': [0.7804027885360186, 0.761425251742835, 0.8160340821068939, 0.620836560805577, 0.642386671832623], 'avgPrecision': 0.7242170710047895, 'recall': [0.7804027885360186, 0.761425251742835, 0.8160340821068939, 0.620836560805577, 0.642386671832623], 'avgRecall': 0.7242170710047895, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.9043377226955848, 0.9388071262587142, 0.9000774593338497, 0.784275755228505, 0.759783029833398], 'avgAccuracy': 0.8574562186700103, 'f1': [0.9058081232777009, 0.9684378745505393, 0.8985338577449483, 0.8790970262643802, 0.8494006558466097], 'avgF1': 0.9002555075368357, 'precision': [0.9043377226955848, 0.9388071262587142, 0.9000774593338497, 0.784275755228505, 0.759783029833398], 'avgPrecision': 0.8574562186700103, 'recall': [0.9043377226955848, 0.9388071262587142, 0.9000774593338497, 0.784275755228505, 0.759783029833398], 'avgRecall': 0.8574562186700103, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgAccuracy': 0.8733372428138536, 'f1': [0.9134793606749531, 0.9749900754267568, 0.9083038949258901, 0.8946917808219178, 0.8648212048724403], 'avgF1': 0.9112572633443916, 'precision': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgPrecision': 0.8733372428138536, 'recall': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgRecall': 0.8733372428138536, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.873337  0.911257   0.873337  0.873337   
1  0.869928  0.908376   0.869928  0.869928   
2  0.716080  0.798170   0.716080  0.716080   
3  0.562276  0.555955   0.562276  0.562276   
4  0.761479  0.830886   0.761479  0.761479   
5  0.871400  0.909807   0.871400  0.871400   
6  0.724217  0.803767   0.724217  0.724217   
7  0.857456  0.900256   0.857456  0.857456   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgAccuracy': 0.8733372428138536, 'f1': [0.9133815972723025, 0.9749900754267568, 0.9083038949258901, 0.8946917808219178, 0.8648271003331741], 'avgF1': 0.9112388897560083, 'precision': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgPrecision': 0.8733372428138536, 'recall': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgRecall': 0.8733372428138536, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.9016266460108443, 0.9341595662277304, 0.9016266460108443, 0.8013168086754454, 0.7733436652460287], 'avgAccuracy': 0.8624146664341786, 'f1': [0.9031920905673471, 0.9659591509811776, 0.9002910214348246, 0.889701139539884, 0.8581618283570202], 'avgF1': 0.9034610461760507, 'precision': [0.9016266460108443, 0.9341595662277304, 0.9016266460108443, 0.8013168086754454, 0.7733436652460287], 'avgPrecision': 0.8624146664341786, 'recall': [0.9016266460108443, 0.9341595662277304, 0.9016266460108443, 0.8013168086754454, 0.7733436652460287], 'avgRecall': 0.8624146664341786, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6123160340821069, 0.5955056179775281], 'avgAccuracy': 0.7180941522554591, 'f1': [0.8270991185513474, 0.8625550660792951, 0.8165922249067556, 0.759548402594283, 0.7318926918225436], 'avgF1': 0.799537500790845, 'precision': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6123160340821069, 0.5955056179775281], 'avgPrecision': 0.7180941522554591, 'recall': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6123160340821069, 0.5955056179775281], 'avgRecall': 0.7180941522554591, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgAccuracy': 0.7614793622344782, 'f1': [0.8198155911067191, 0.8781229632848142, 0.8166686000561928, 0.8314098212265219, 0.8084146843926965], 'avgF1': 0.8308863320133889, 'precision': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgPrecision': 0.7614793622344782, 'recall': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgRecall': 0.7614793622344782, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.9047250193648335, 0.9512006196746708, 0.9093725793958172, 0.8071262587141751, 0.7822549399457575], 'avgAccuracy': 0.8709358834190508, 'f1': [0.9058226669293736, 0.9749900754267568, 0.907922863761689, 0.8932704672096015, 0.8638521812514545], 'avgF1': 0.909171650915775, 'precision': [0.9047250193648335, 0.9512006196746708, 0.9093725793958172, 0.8071262587141751, 0.7822549399457575], 'avgPrecision': 0.8709358834190508, 'recall': [0.9047250193648335, 0.9512006196746708, 0.9093725793958172, 0.8071262587141751, 0.7822549399457575], 'avgRecall': 0.8709358834190508, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7796281951975214, 0.7687838884585593, 0.8160340821068939, 0.6134779240898528, 0.5974428516079039], 'avgAccuracy': 0.7150733882921463, 'f1': [0.805336920369519, 0.8692796146266697, 0.8139814356233989, 0.7604416706673068, 0.733128262891943], 'avgF1': 0.7964335808357674, 'precision': [0.7796281951975214, 0.7687838884585593, 0.8160340821068939, 0.6134779240898528, 0.5974428516079039], 'avgPrecision': 0.7150733882921463, 'recall': [0.7796281951975214, 0.7687838884585593, 0.8160340821068939, 0.6134779240898528, 0.5974428516079039], 'avgRecall': 0.7150733882921463, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.9024012393493416, 0.9384198295894656, 0.9004647560030984, 0.7835011618900077, 0.7593955831073227], 'avgAccuracy': 0.8568365139878472, 'f1': [0.9042683325944265, 0.9682317682317682, 0.8986047311033807, 0.8786102062975025, 0.8491306029432546], 'avgF1': 0.8997691282340665, 'precision': [0.9024012393493416, 0.9384198295894656, 0.9004647560030984, 0.7835011618900077, 0.7593955831073227], 'avgPrecision': 0.8568365139878472, 'recall': [0.9024012393493416, 0.9384198295894656, 0.9004647560030984, 0.7835011618900077, 0.7593955831073227], 'avgRecall': 0.8568365139878472, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgAccuracy': 0.8733372428138536, 'f1': [0.9133815972723025, 0.9749900754267568, 0.9083038949258901, 0.8946917808219178, 0.8648271003331741], 'avgF1': 0.9112388897560083, 'precision': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgPrecision': 0.8733372428138536, 'recall': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgRecall': 0.8733372428138536, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.873337  0.911239   0.873337  0.873337   
1  0.862415  0.903461   0.862415  0.862415   
2  0.718094  0.799538   0.718094  0.718094   
3  0.562276  0.555955   0.562276  0.562276   
4  0.761479  0.830886   0.761479  0.761479   
5  0.870936  0.909172   0.870936  0.870936   
6  0.715073  0.796434   0.715073  0.715073   
7  0.856837  0.899769   0.856837  0.856837   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgAccuracy': 0.871632777332776, 'f1': [0.9129489803012953, 0.9749900754267568, 0.905865172416312, 0.8939815806382522, 0.8618786720632232], 'avgF1': 0.909932896169168, 'precision': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgPrecision': 0.871632777332776, 'recall': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgRecall': 0.871632777332776, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.9144074360960496, 0.9368706429124709, 0.907436096049574, 0.8013168086754454, 0.7702440914374273], 'avgAccuracy': 0.8660550150341935, 'f1': [0.9136219438937164, 0.9674065186962608, 0.9058128139987781, 0.889701139539884, 0.8561744926373911], 'avgF1': 0.906543381753206, 'precision': [0.9144074360960496, 0.9368706429124709, 0.907436096049574, 0.8013168086754454, 0.7702440914374273], 'avgPrecision': 0.8660550150341935, 'recall': [0.9144074360960496, 0.9368706429124709, 0.907436096049574, 0.8013168086754454, 0.7702440914374273], 'avgRecall': 0.8660550150341935, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 14, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6119287374128582, 0.5955056179775281], 'avgAccuracy': 0.7180166929216094, 'f1': [0.8270991185513474, 0.8625550660792951, 0.8165922249067556, 0.7592503604036521, 0.7318926918225436], 'avgF1': 0.7994778923527188, 'precision': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6119287374128582, 0.5955056179775281], 'avgPrecision': 0.7180166929216094, 'recall': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6119287374128582, 0.5955056179775281], 'avgRecall': 0.7180166929216094, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.8009295120061968, 0.7823392718822618, 0.8175832687838884, 0.7099147947327653, 0.6997287872917474], 'avgAccuracy': 0.762099126939372, 'f1': [0.8228027997729285, 0.8778791829639285, 0.8166686000561928, 0.8303510758776897, 0.8092211059284697], 'avgF1': 0.8313845529198418, 'precision': [0.8009295120061968, 0.7823392718822618, 0.8175832687838884, 0.7099147947327653, 0.6997287872917474], 'avgPrecision': 0.762099126939372, 'recall': [0.8009295120061968, 0.7823392718822618, 0.8175832687838884, 0.7099147947327653, 0.6997287872917474], 'avgRecall': 0.762099126939372, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.9089852827265685, 0.9512006196746708, 0.9066615027110767, 0.8024786986831913, 0.774118558698179], 'avgAccuracy': 0.8686889324987372, 'f1': [0.9091471938599553, 0.9749900754267568, 0.9050511083456165, 0.8904168457241083, 0.858657640209762], 'avgF1': 0.9076525727132397, 'precision': [0.9089852827265685, 0.9512006196746708, 0.9066615027110767, 0.8024786986831913, 0.774118558698179], 'avgPrecision': 0.8686889324987372, 'recall': [0.9089852827265685, 0.9512006196746708, 0.9066615027110767, 0.8024786986831913, 0.774118558698179], 'avgRecall': 0.8686889324987372, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.7796281951975214, 0.7668474051123161, 0.814872192099148, 0.6103795507358637, 0.5939558310732275], 'avgAccuracy': 0.7131366348436153, 'f1': [0.805336920369519, 0.8680403331871986, 0.8127836382107109, 0.7580567580567581, 0.7303740855092412], 'avgF1': 0.7949183470666855, 'precision': [0.7796281951975214, 0.7668474051123161, 0.814872192099148, 0.6103795507358637, 0.5939558310732275], 'avgPrecision': 0.7131366348436153, 'recall': [0.7796281951975214, 0.7668474051123161, 0.814872192099148, 0.6103795507358637, 0.5939558310732275], 'avgRecall': 0.7131366348436153, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.8934934159566228, 0.930286599535244, 0.8938807126258714, 0.7819519752130132, 0.7528089887640449], 'avgAccuracy': 0.8504843384189592, 'f1': [0.8966769958192552, 0.963884430176565, 0.8919130556138197, 0.8776352966746359, 0.844829384749791], 'avgF1': 0.8949878326068134, 'precision': [0.8934934159566228, 0.930286599535244, 0.8938807126258714, 0.7819519752130132, 0.7528089887640449], 'avgPrecision': 0.8504843384189592, 'recall': [0.8934934159566228, 0.930286599535244, 0.8938807126258714, 0.7819519752130132, 0.7528089887640449], 'avgRecall': 0.8504843384189592, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgAccuracy': 0.871632777332776, 'f1': [0.9129489803012953, 0.9749900754267568, 0.905865172416312, 0.8939815806382522, 0.8618786720632232], 'avgF1': 0.909932896169168, 'precision': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgPrecision': 0.871632777332776, 'recall': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgRecall': 0.871632777332776, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.871633  0.909933   0.871633  0.871633   
1  0.866055  0.906543   0.866055  0.866055   
2  0.718017  0.799478   0.718017  0.718017   
3  0.562276  0.555955   0.562276  0.562276   
4  0.762099  0.831385   0.762099  0.762099   
5  0.868689  0.907653   0.868689  0.868689   
6  0.713137  0.794918   0.713137  0.713137   
7  0.850484  0.894988   0.850484  0.850484   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgAccuracy': 0.8707807246604289, 'f1': [0.910617074792847, 0.9749900754267568, 0.904927397758066, 0.8937446443873178, 0.861862044195941], 'avgF1': 0.9092282473121858, 'precision': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgPrecision': 0.8707807246604289, 'recall': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgRecall': 0.8707807246604289, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.9054996127033308, 0.9589465530596437, 0.9043377226955848, 0.8001549186676995, 0.771793878341728], 'avgAccuracy': 0.8681465370935973, 'f1': [0.9065883363039315, 0.9790431000395413, 0.9029503227136623, 0.8889845094664374, 0.857168979814244], 'avgF1': 0.9069470496675633, 'precision': [0.9054996127033308, 0.9589465530596437, 0.9043377226955848, 0.8001549186676995, 0.771793878341728], 'avgPrecision': 0.8681465370935973, 'recall': [0.9054996127033308, 0.9589465530596437, 0.9043377226955848, 0.8001549186676995, 0.771793878341728], 'avgRecall': 0.8681465370935973, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7986057319907048, 0.7540666150271108, 0.8171959721146398, 0.6026336173508908, 0.5900813638124758], 'avgAccuracy': 0.7125166600591644, 'f1': [0.8206411285065356, 0.8597924486641644, 0.8162220567606543, 0.7520541324311262, 0.7276013289453526], 'avgF1': 0.7952622190615666, 'precision': [0.7986057319907048, 0.7540666150271108, 0.8171959721146398, 0.6026336173508908, 0.5900813638124758], 'avgPrecision': 0.7125166600591644, 'recall': [0.7986057319907048, 0.7540666150271108, 0.8171959721146398, 0.6026336173508908, 0.5900813638124758], 'avgRecall': 0.7125166600591644, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5623536233171502, 'f1': [0.23210809566060528, 0.20445062586926283, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5560801815380465, 'precision': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5623536233171502, 'recall': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5623536233171502, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7993803253292022, 0.7776917118512781, 0.8113865220759101, 0.7149496514329977, 0.6912049593180938], 'avgAccuracy': 0.7589226340014964, 'f1': [0.8215160665131502, 0.8749455337690631, 0.8102413246989624, 0.8337850045167119, 0.8030842271732835], 'avgF1': 0.8287144313342343, 'precision': [0.7993803253292022, 0.7776917118512781, 0.8113865220759101, 0.7149496514329977, 0.6912049593180938], 'avgPrecision': 0.7589226340014964, 'recall': [0.7993803253292022, 0.7776917118512781, 0.8113865220759101, 0.7149496514329977, 0.6912049593180938], 'avgRecall': 0.7589226340014964, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.9035631293570875, 0.9512006196746708, 0.9043377226955848, 0.8059643687064292, 0.7768306857807051], 'avgAccuracy': 0.8683793052428955, 'f1': [0.9050454360167915, 0.9749900754267568, 0.9029503227136623, 0.8925584387733219, 0.8603801813279701], 'avgF1': 0.9071848908517005, 'precision': [0.9035631293570875, 0.9512006196746708, 0.9043377226955848, 0.8059643687064292, 0.7768306857807051], 'avgPrecision': 0.8683793052428955, 'recall': [0.9035631293570875, 0.9512006196746708, 0.9043377226955848, 0.8059643687064292, 0.7768306857807051], 'avgRecall': 0.8683793052428955, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7807900852052673, 0.7645236250968241, 0.8121611154144074, 0.6096049573973664, 0.6334753971328942], 'avgAccuracy': 0.7201110360493519, 'f1': [0.80631773797358, 0.8665496049165935, 0.8105596685886568, 0.757459095283927, 0.7609770506087514], 'avgF1': 0.8003726314743017, 'precision': [0.7807900852052673, 0.7645236250968241, 0.8121611154144074, 0.6096049573973664, 0.6334753971328942], 'avgPrecision': 0.7201110360493519, 'recall': [0.7807900852052673, 0.7645236250968241, 0.8121611154144074, 0.6096049573973664, 0.6334753971328942], 'avgRecall': 0.7201110360493519, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.9051123160340822, 0.9275755228505035, 0.888845855925639, 0.7738187451587917, 0.7462223944207671], 'avgAccuracy': 0.8483149668779567, 'f1': [0.9059391834928153, 0.9624271649588104, 0.8866709665438921, 0.8724890829694323, 0.84044762324625], 'avgF1': 0.89359480424224, 'precision': [0.9051123160340822, 0.9275755228505035, 0.888845855925639, 0.7738187451587917, 0.7462223944207671], 'avgPrecision': 0.8483149668779567, 'recall': [0.9051123160340822, 0.9275755228505035, 0.888845855925639, 0.7738187451587917, 0.7462223944207671], 'avgRecall': 0.8483149668779567, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgAccuracy': 0.8707807246604289, 'f1': [0.910617074792847, 0.9749900754267568, 0.904927397758066, 0.8937446443873178, 0.861862044195941], 'avgF1': 0.9092282473121858, 'precision': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgPrecision': 0.8707807246604289, 'recall': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgRecall': 0.8707807246604289, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.870781  0.909228   0.870781  0.870781   
1  0.868147  0.906947   0.868147  0.868147   
2  0.712517  0.795262   0.712517  0.712517   
3  0.562354  0.556080   0.562354  0.562354   
4  0.758923  0.828714   0.758923  0.758923   
5  0.868379  0.907185   0.868379  0.868379   
6  0.720111  0.800373   0.720111  0.720111   
7  0.848315  0.893595   0.848315  0.848315   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgAccuracy': 0.8681470172754422, 'f1': [0.9089591438613208, 0.9727471653073403, 0.9033304862958237, 0.8911316298045953, 0.8611215657346356], 'avgF1': 0.9074579982007431, 'precision': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgPrecision': 0.8681470172754422, 'recall': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgRecall': 0.8681470172754422, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.9047250193648335, 0.9264136328427576, 0.9031758326878389, 0.7467079783113865, 0.7659821774506005], 'avgAccuracy': 0.8494009281314834, 'f1': [0.9060333350386341, 0.9618013671089667, 0.9020107293732391, 0.8549889135254989, 0.8534311499792596], 'avgF1': 0.8956530990051197, 'precision': [0.9047250193648335, 0.9264136328427576, 0.9031758326878389, 0.7467079783113865, 0.7659821774506005], 'avgPrecision': 0.8494009281314834, 'recall': [0.9047250193648335, 0.9264136328427576, 0.9031758326878389, 0.7467079783113865, 0.7659821774506005], 'avgRecall': 0.8494009281314834, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 16, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7893106119287374, 0.7316034082106894, 0.813710302091402, 0.6041828040278854, 0.5916311507167764], 'avgAccuracy': 0.7060876553950981, 'f1': [0.8133089364082086, 0.8450011183180496, 0.8122921048657172, 0.7532592950265572, 0.7288304256934545], 'avgF1': 0.7905383760623974, 'precision': [0.7893106119287374, 0.7316034082106894, 0.813710302091402, 0.6041828040278854, 0.5916311507167764], 'avgPrecision': 0.7060876553950981, 'recall': [0.7893106119287374, 0.7316034082106894, 0.813710302091402, 0.6041828040278854, 0.5916311507167764], 'avgRecall': 0.7060876553950981, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5623536233171502, 'f1': [0.23210809566060528, 0.20445062586926283, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5560801815380465, 'precision': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5623536233171502, 'recall': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5623536233171502, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7831138652207591, 0.7796281951975214, 0.8125484120836561, 0.7006196746707978, 0.694304533126695], 'avgAccuracy': 0.7540429360598859, 'f1': [0.8082803494249249, 0.8761697497279651, 0.8115102256268, 0.8239580961056706, 0.8053049218925732], 'avgF1': 0.8250446685555868, 'precision': [0.7831138652207591, 0.7796281951975214, 0.8125484120836561, 0.7006196746707978, 0.694304533126695], 'avgPrecision': 0.7540429360598859, 'recall': [0.7831138652207591, 0.7796281951975214, 0.8125484120836561, 0.7006196746707978, 0.694304533126695], 'avgRecall': 0.7540429360598859, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.9058869093725794, 0.9465530596436871, 0.9039504260263361, 0.7982184353214562, 0.7729562185199536], 'avgAccuracy': 0.8655130097768025, 'f1': [0.9072308539360908, 0.9725427775567052, 0.9025445552900987, 0.8877880680594443, 0.8578784379915173], 'avgF1': 0.9055969385667713, 'precision': [0.9058869093725794, 0.9465530596436871, 0.9039504260263361, 0.7982184353214562, 0.7729562185199536], 'avgPrecision': 0.8655130097768025, 'recall': [0.9058869093725794, 0.9465530596436871, 0.9039504260263361, 0.7982184353214562, 0.7729562185199536], 'avgRecall': 0.8655130097768025, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7792408985282726, 0.7652982184353214, 0.8106119287374128, 0.6080557707203718, 0.6385122045718714], 'avgAccuracy': 0.72034380419865, 'f1': [0.8047639669500705, 0.8670469504168494, 0.8087749101136529, 0.75626204238921, 0.7648348961392571], 'avgF1': 0.800336553201808, 'precision': [0.7792408985282726, 0.7652982184353214, 0.8106119287374128, 0.6080557707203718, 0.6385122045718714], 'avgPrecision': 0.72034380419865, 'recall': [0.7792408985282726, 0.7652982184353214, 0.8106119287374128, 0.6080557707203718, 0.6385122045718714], 'avgRecall': 0.72034380419865, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.8915569326103796, 0.9078233927188226, 0.8900077459333849, 0.778853601859024, 0.7493219682293685], 'avgAccuracy': 0.843512728270196, 'f1': [0.8954807035948079, 0.9516849370686156, 0.8880317078810531, 0.8756803831918136, 0.8424693327575392], 'avgF1': 0.8906694128987659, 'precision': [0.8915569326103796, 0.9078233927188226, 0.8900077459333849, 0.778853601859024, 0.7493219682293685], 'avgPrecision': 0.843512728270196, 'recall': [0.8915569326103796, 0.9078233927188226, 0.8900077459333849, 0.778853601859024, 0.7493219682293685], 'avgRecall': 0.843512728270196, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgAccuracy': 0.8681470172754422, 'f1': [0.9089591438613208, 0.9727471653073403, 0.9033304862958237, 0.8911316298045953, 0.8611215657346356], 'avgF1': 0.9074579982007431, 'precision': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgPrecision': 0.8681470172754422, 'recall': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgRecall': 0.8681470172754422, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.868147  0.907458   0.868147  0.868147   
1  0.849401  0.895653   0.849401  0.849401   
2  0.706088  0.790538   0.706088  0.706088   
3  0.562354  0.556080   0.562354  0.562354   
4  0.754043  0.825045   0.754043  0.754043   
5  0.865513  0.905597   0.865513  0.865513   
6  0.720344  0.800337   0.720344  0.720344   
7  0.843513  0.890669   0.843513  0.843513   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgAccuracy': 0.8528078183207981, 'f1': [0.9022114095895609, 0.9723383084577115, 0.8900492682245151, 0.8737186477644493, 0.8422848050693988], 'avgF1': 0.8961204878211272, 'precision': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgPrecision': 0.8528078183207981, 'recall': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgRecall': 0.8528078183207981, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.9155693261037955, 0.9457784663051898, 0.8911696359411309, 0.7234701781564679, 0.7446726075164665], 'avgAccuracy': 0.8441320428046101, 'f1': [0.9131760617034314, 0.9721337579617836, 0.8895032429297922, 0.8395505617977529, 0.8394983217203529], 'avgF1': 0.8907723892226226, 'precision': [0.9155693261037955, 0.9457784663051898, 0.8911696359411309, 0.7234701781564679, 0.7446726075164665], 'avgPrecision': 0.8441320428046101, 'recall': [0.9155693261037955, 0.9457784663051898, 0.8911696359411309, 0.7234701781564679, 0.7446726075164665], 'avgRecall': 0.8441320428046101, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.7726568551510457, 0.7773044151820294, 0.7997676219984509, 0.5945003872966692, 0.5769081751259202], 'avgAccuracy': 0.704227490950823, 'f1': [0.8003500340001569, 0.8747003704510786, 0.7993560957994182, 0.7456886082098615, 0.7167332306608132], 'avgF1': 0.7873656678242656, 'precision': [0.7726568551510457, 0.7773044151820294, 0.7997676219984509, 0.5945003872966692, 0.5769081751259202], 'avgPrecision': 0.704227490950823, 'recall': [0.7726568551510457, 0.7773044151820294, 0.7997676219984509, 0.5945003872966692, 0.5769081751259202], 'avgRecall': 0.704227490950823, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5623536233171502, 'f1': [0.23210809566060528, 0.20445062586926283, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5560801815380465, 'precision': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5623536233171502, 'recall': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5623536233171502, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.7989930286599535, 0.7796281951975214, 0.801704105344694, 0.703718048024787, 0.6838434715226657], 'avgAccuracy': 0.7535773697499243, 'f1': [0.8198695777300405, 0.8761697497279651, 0.8013882497041634, 0.8260968401909524, 0.7978933029226667], 'avgF1': 0.8242835440551577, 'precision': [0.7989930286599535, 0.7796281951975214, 0.801704105344694, 0.703718048024787, 0.6838434715226657], 'avgPrecision': 0.7535773697499243, 'recall': [0.7989930286599535, 0.7796281951975214, 0.801704105344694, 0.703718048024787, 0.6838434715226657], 'avgRecall': 0.7535773697499243, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.8993028659953525, 0.9461657629744384, 0.8903950426026336, 0.772269558481797, 0.7477721813250678], 'avgAccuracy': 0.8511810822758579, 'f1': [0.9001232520618444, 0.9723383084577115, 0.8884729136470888, 0.8715034965034966, 0.8414954182769057], 'avgF1': 0.8947866777894093, 'precision': [0.8993028659953525, 0.9461657629744384, 0.8903950426026336, 0.772269558481797, 0.7477721813250678], 'avgPrecision': 0.8511810822758579, 'recall': [0.8993028659953525, 0.9461657629744384, 0.8903950426026336, 0.772269558481797, 0.7477721813250678], 'avgRecall': 0.8511810822758579, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.7668474051123161, 0.7664601084430674, 0.7900852052672347, 0.6034082106893881, 0.5749709414955444], 'avgAccuracy': 0.7003543742015101, 'f1': [0.7956388374535504, 0.8677921508441132, 0.7891835710619003, 0.7526570048309179, 0.7147264846694119], 'avgF1': 0.7839996097719787, 'precision': [0.7668474051123161, 0.7664601084430674, 0.7900852052672347, 0.6034082106893881, 0.5749709414955444], 'avgPrecision': 0.7003543742015101, 'recall': [0.7668474051123161, 0.7664601084430674, 0.7900852052672347, 0.6034082106893881, 0.5749709414955444], 'avgRecall': 0.7003543742015101, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.8702556158017041, 0.9217660728117738, 0.8667699457784663, 0.7223082881487219, 0.7047655947307245], 'avgAccuracy': 0.8171731034542782, 'f1': [0.8763107903750196, 0.959290608625554, 0.8648554744990689, 0.8387677085675735, 0.8124433204575152], 'avgF1': 0.8703335805049462, 'precision': [0.8702556158017041, 0.9217660728117738, 0.8667699457784663, 0.7223082881487219, 0.7047655947307245], 'avgPrecision': 0.8171731034542782, 'recall': [0.8702556158017041, 0.9217660728117738, 0.8667699457784663, 0.7223082881487219, 0.7047655947307245], 'avgRecall': 0.8171731034542782, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgAccuracy': 0.8528078183207981, 'f1': [0.9022114095895609, 0.9723383084577115, 0.8900492682245151, 0.8737186477644493, 0.8422848050693988], 'avgF1': 0.8961204878211272, 'precision': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgPrecision': 0.8528078183207981, 'recall': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgRecall': 0.8528078183207981, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.852808  0.896120   0.852808  0.852808   
1  0.844132  0.890772   0.844132  0.844132   
2  0.704227  0.787366   0.704227  0.704227   
3  0.562354  0.556080   0.562354  0.562354   
4  0.753577  0.824284   0.753577  0.753577   
5  0.851181  0.894787   0.851181  0.851181   
6  0.700354  0.784000   0.700354  0.700354   
7  0.817173  0.870334   0.817173  0.817173   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'brute', 'leaf_size': 30, 'metri...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result: 
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgAccuracy': 0.8528852476432826, 'f1': [0.9022114095895609, 0.9723383084577115, 0.8908068506388271, 0.8737186477644493, 0.8420297532151674], 'avgF1': 0.8962209939331433, 'precision': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgPrecision': 0.8528852476432826, 'recall': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgRecall': 0.8528852476432826, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result: 
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.9252517428350117, 0.9910921766072812, 0.87141750580945, 0.663439194422928, 0.6458736923672995], 'avgAccuracy': 0.8194148624083941, 'f1': [0.9172195641892283, 0.9955261622252479, 0.8653575275121729, 0.7976717112922003, 0.7702454308694038], 'avgF1': 0.8692040792176506, 'precision': [0.9252517428350117, 0.9910921766072812, 0.87141750580945, 0.663439194422928, 0.6458736923672995], 'avgPrecision': 0.8194148624083941, 'recall': [0.9252517428350117, 0.9910921766072812, 0.87141750580945, 0.663439194422928, 0.6458736923672995], 'avgRecall': 0.8194148624083941, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************

Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result: 
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7730441518202944, 0.7780790085205267, 0.7993803253292022, 0.5941130906274206, 0.5769081751259202], 'avgAccuracy': 0.7043049502846728, 'f1': [0.8006471460744299, 0.8751905902853409, 0.7984777645297028, 0.7453838678328474, 0.7167332306608132], 'avgF1': 0.7872865198766268, 'precision': [0.7730441518202944, 0.7780790085205267, 0.7993803253292022, 0.5941130906274206, 0.5769081751259202], 'avgPrecision': 0.7043049502846728, 'recall': [0.7730441518202944, 0.7780790085205267, 0.7993803253292022, 0.5941130906274206, 0.5769081751259202], 'avgRecall': 0.7043049502846728, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************

Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result: 
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7478698683191325, 0.7548412083656081, 0.7641363284275755, 0.679705654531371, 0.654010073614878], 'avgAccuracy': 0.720112626651713, 'f1': [0.7820267569039114, 0.8602957404546456, 0.7642360198261849, 0.8093151948351396, 0.7764561954959115], 'avgF1': 0.7984659815031586, 'precision': [0.7478698683191325, 0.7548412083656081, 0.7641363284275755, 0.679705654531371, 0.654010073614878], 'avgPrecision': 0.720112626651713, 'recall': [0.7478698683191325, 0.7548412083656081, 0.7641363284275755, 0.679705654531371, 0.654010073614878], 'avgRecall': 0.720112626651713, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************

Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result: 
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7989930286599535, 0.7796281951975214, 0.8036405886909372, 0.7017815646785438, 0.6819062378922898], 'avgAccuracy': 0.7531899230238491, 'f1': [0.8198695777300405, 0.8761697497279651, 0.803125804689984, 0.8247610377787892, 0.7965198184597836], 'avgF1': 0.8240891976773125, 'precision': [0.7989930286599535, 0.7796281951975214, 0.8036405886909372, 0.7017815646785438, 0.6819062378922898], 'avgPrecision': 0.7531899230238491, 'recall': [0.7989930286599535, 0.7796281951975214, 0.8036405886909372, 0.7017815646785438, 0.6819062378922898], 'avgRecall': 0.7531899230238491, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************

Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result: 
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.8993028659953525, 0.9438419829589465, 0.8915569326103796, 0.7749806351665376, 0.7454475009686168], 'avgAccuracy': 0.8510259835399666, 'f1': [0.8998928645511427, 0.971109782825264, 0.8896705786217454, 0.8732271437922758, 0.8399854284829621], 'avgF1': 0.894777159654678, 'precision': [0.8993028659953525, 0.9438419829589465, 0.8915569326103796, 0.7749806351665376, 0.7454475009686168], 'avgPrecision': 0.8510259835399666, 'recall': [0.8993028659953525, 0.9438419829589465, 0.8915569326103796, 0.7749806351665376, 0.7454475009686168], 'avgRecall': 0.8510259835399666, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************

Processing Model: SVC
*****************************************************
* SVC
* Best Params Result: 
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7668474051123161, 0.7668474051123161, 0.7877614252517429, 0.6502711076684741, 0.6365749709414955], 'avgAccuracy': 0.7216604628172689, 'f1': [0.7956388374535504, 0.8680403331871986, 0.7870196635072528, 0.7880779159821638, 0.7633072687128298], 'avgF1': 0.8004168037685991, 'precision': [0.7668474051123161, 0.7668474051123161, 0.7877614252517429, 0.6502711076684741, 0.6365749709414955], 'avgPrecision': 0.7216604628172689, 'recall': [0.7668474051123161, 0.7668474051123161, 0.7877614252517429, 0.6502711076684741, 0.6365749709414955], 'avgRecall': 0.7216604628172689, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************

Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result: 
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.8783888458559257, 0.8973663826491092, 0.8702556158017041, 0.7207591014717274, 0.717551336691205], 'avgAccuracy': 0.8168642564939342, 'f1': [0.882789074745606, 0.9459073280261276, 0.8677169818543689, 0.8377222597344136, 0.8211514397895884], 'avgF1': 0.8710574168300209, 'precision': [0.8783888458559257, 0.8973663826491092, 0.8702556158017041, 0.7207591014717274, 0.717551336691205], 'avgPrecision': 0.8168642564939342, 'recall': [0.8783888458559257, 0.8973663826491092, 0.8702556158017041, 0.7207591014717274, 0.717551336691205], 'avgRecall': 0.8168642564939342, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgAccuracy': 0.8528852476432826, 'f1': [0.9022114095895609, 0.9723383084577115, 0.8908068506388271, 0.8737186477644493, 0.8420297532151674], 'avgF1': 0.8962209939331433, 'precision': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgPrecision': 0.8528852476432826, 'recall': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgRecall': 0.8528852476432826, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************

                    model                                           features  \
0  RandomForestClassifier  Marked & transmucosal increase in lamina propr...   
1    KNeighborsClassifier  Marked & transmucosal increase in lamina propr...   
2      LogisticRegression  Marked & transmucosal increase in lamina propr...   
3              GaussianNB  Marked & transmucosal increase in lamina propr...   
4      AdaBoostClassifier  Marked & transmucosal increase in lamina propr...   
5  DecisionTreeClassifier  Marked & transmucosal increase in lamina propr...   
6                     SVC  Marked & transmucosal increase in lamina propr...   
7           MLPClassifier  Marked & transmucosal increase in lamina propr...   

   accuracy        f1  precision    recall  \
0  0.852885  0.896221   0.852885  0.852885   
1  0.819415  0.869204   0.819415  0.819415   
2  0.704305  0.787287   0.704305  0.704305   
3  0.720113  0.798466   0.720113  0.720113   
4  0.753190  0.824089   0.753190  0.753190   
5  0.851026  0.894777   0.851026  0.851026   
6  0.721660  0.800417   0.721660  0.721660   
7  0.816864  0.871057   0.816864  0.816864   

                                              params  
0  {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...  
1  {'algorithm': 'auto', 'leaf_size': 30, 'metric...  
2  {'C': 1, 'class_weight': None, 'dual': False, ...  
3           {'priors': None, 'var_smoothing': 1e-09}  
4  {'algorithm': 'SAMME.R', 'base_estimator': Non...  
5  {'ccp_alpha': 0.0, 'class_weight': None, 'crit...  
6  {'C': 1.0, 'break_ties': False, 'cache_size': ...  
7  {'activation': 'logistic', 'alpha': 0.0001, 'b...  

now = datetime.datetime.now()
print ("Current date and time : ")
print (now.strftime("%Y-%m-%d %H:%M:%S"))

Current date and time : 
2021-06-06 04:16:12

Creation of novel ML Models

Running Models

Results

smotePrintoutBytes = open('smotePrintout_onlyibd.txt','r')
smotePrintout      = smotePrintoutBytes.read()
smotePrintout[:100]

'********************************************\nStarting SMOTE data set....\n***************************'

originalPrintoutBytes = open('originalDatasetPrintout_onlyibd.txt','r')
originalPrintout      = originalPrintoutBytes.read()
originalPrintout[:100]

'********************************************\nStarting Original data set....\n************************'

msmotePrintoutBytes = open('msmotePrintout_onlyibd.txt','r')
msmotePrintout      = msmotePrintoutBytes.read()
msmotePrintout[:100]

'********************************************\nStarting MSMOTE data set....\n**************************'

'''
Using the printout from the SMOTE and original runs,
grab the dictionaries that match this format
{'classifier':'RandomForestClassifier','features':'Feature1, Feature2'}
'''
smoteModelDictionaries = re.findall('Best Params Result: \n\* \{([^}]+)\}',smotePrintout)
originalModelDictionaries = re.findall('Best Params Result: \n\* \{([^}]+)\}',originalPrintout)
msmoteModelDictionaries = re.findall('Best Params Result: \n\* \{([^}]+)\}',msmotePrintout)

'''
each dictionary is in format of 'key':'value' or 'key':[values] or 'key': 0.0002 or 'key': None

get the classifier: (text is here) ..... avgRecall : (text is here) .... avgF1 : (text is here)
'''
def getMetricsForAllModels(modelDictionaries, smote='smote'):
    listOfDicts = []
    for dictionary in modelDictionaries:
        keys   = ['classifier','avgAccuracy','avgF1','avgPrecision','avgRecall']
        values = re.findall("'classifier': '([^']+)'.+'avgAccuracy': ([.\d]+).+'avgF1': ([.\d]+).+'avgPrecision': ([.\d]+).+'avgRecall': ([.\d]+)",dictionary)[0]
        dictionary = dict(zip(keys,values))
        dictionary['smote'] = smote
        listOfDicts.append(dictionary)
    return listOfDicts

smoteDictList    = getMetricsForAllModels(smoteModelDictionaries,'smote')
originalDictList = getMetricsForAllModels(originalModelDictionaries,'no smote')
msmoteDictList    = getMetricsForAllModels(msmoteModelDictionaries,'msmote')

def createModelCompareDf(dictList):
    modelCompare = pd.DataFrame(columns = ['classifier','avgAccuracy','avgF1','avgPrecision','avgRecall'])
    for dictionary in dictList:
        modelCompare = modelCompare.append(dictionary, ignore_index=True)
    return modelCompare

smoteCompareDf = createModelCompareDf(smoteDictList)
originalCompareDf = createModelCompareDf(originalDictList)
msmoteCompareDf = createModelCompareDf(msmoteDictList)
modelCompare    = pd.concat([smoteCompareDf, originalCompareDf,msmoteCompareDf], ignore_index=True)
modelCompare.head()

	classifier	avgAccuracy	avgF1	avgPrecision	avgRecall	smote
0	RandomForestClassifier	0.778552920071756	0.7952724325649522	0.778552920071756	0.778552920071756	smote
1	KNeighborsClassifier	0.7462959271809182	0.77386163218242	0.7462959271809182	0.7462959271809182	smote
2	LogisticRegression	0.648169556840077	0.692048322178302	0.648169556840077	0.648169556840077	smote
3	GaussianNB	0.5866985582353332	0.5370210108736294	0.5866985582353332	0.5866985582353332	smote
4	AdaBoostClassifier	0.7207893163244967	0.7549521900542933	0.7207893163244967	0.7207893163244967	smote
...	...	...	...	...	...	...
403	GaussianNB	0.720112626651713	0.7984659815031586	0.720112626651713	0.720112626651713	msmote
404	AdaBoostClassifier	0.7531899230238491	0.8240891976773125	0.7531899230238491	0.7531899230238491	msmote
405	DecisionTreeClassifier	0.8510259835399666	0.894777159654678	0.8510259835399666	0.8510259835399666	msmote
406	SVC	0.7216604628172689	0.8004168037685991	0.7216604628172689	0.7216604628172689	msmote
407	MLPClassifier	0.8168642564939342	0.8710574168300209	0.8168642564939342	0.8168642564939342	msmote

408 rows × 6 columns

modelCompare[['avgAccuracy','avgF1','avgPrecision','avgRecall']] = modelCompare[['avgAccuracy','avgF1','avgPrecision','avgRecall']].astype(float)

bestModels = pd.merge(modelCompare[modelCompare['smote']=='smote'], modelCompare[modelCompare['smote']=='smote'].groupby('classifier')['avgAccuracy'].max().reset_index(), on=['classifier','avgAccuracy'])
bestModelsNo = pd.merge(modelCompare[modelCompare['smote']=='no smote'], modelCompare[modelCompare['smote']=='no smote'].groupby('classifier')['avgAccuracy'].max().reset_index(), on=['classifier','avgAccuracy'])
bestModelsM = pd.merge(modelCompare[modelCompare['smote']=='msmote'], modelCompare[modelCompare['smote']=='msmote'].groupby('classifier')['avgAccuracy','avgF1'].max().reset_index(), on=['classifier','avgAccuracy','avgF1'])

<ipython-input-277-a0afa624f181>:3: FutureWarning:

Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.

rotation = 90

fig,ax=plt.subplots(nrows=2,ncols=2,figsize=(20,15))
plt.subplots_adjust(hspace=0.5)
ax[0][0].scatter(bestModels['classifier'].unique(),bestModels['avgAccuracy'].unique(),label='smote')
ax[0][0].scatter(bestModelsNo['classifier'].unique(),bestModelsNo['avgAccuracy'].unique(),label='no smote')
ax[0][0].scatter(bestModelsM['classifier'].unique(),bestModelsM['avgAccuracy'].unique(),label='msmote')
ax[0][0].tick_params(rotation=rotation)
ax[0][0].set(title='Best Accuracy for each Model')

ax[0][1].scatter(bestModels['classifier'].unique(),bestModels['avgRecall'].unique(),label='smote')
ax[0][1].scatter(bestModelsNo['classifier'].unique(),bestModelsNo['avgRecall'].unique(),label='no smote')
ax[0][1].scatter(bestModelsM['classifier'].unique(),bestModelsM['avgRecall'].unique(),label='msmote')
ax[0][1].tick_params(rotation=rotation)
ax[0][1].set(title='Recall(Sensitivity) for Models with best Accuracy')
ax[0][1].legend()

ax[1][0].scatter(bestModels['classifier'].unique(),bestModels['avgF1'].unique(),
label='smote')
ax[1][0].scatter(bestModelsNo['classifier'].unique(),bestModelsNo['avgF1'].unique(),label='no smote')
ax[1][0].scatter(bestModelsM['classifier'].unique(),bestModelsM['avgF1'].unique(),label='msmote')
ax[1][0].tick_params(rotation=rotation)
ax[1][0].set(title='F1 for Models with best Accuracy')
ax[1][0].legend()

for classifier in modelCompare['classifier'].unique():
    subdf = modelCompare[modelCompare['classifier']==classifier]
    ax[1][1].scatter(subdf['avgF1'],subdf['avgAccuracy'],label=classifier)
ax[1][1].set(xlabel='F1',ylabel='avgAccuracy',title='Each point is the Average of 5 fold Runs for each algorithm at a specific feature set/parameter set')
ax[1][1].legend(bbox_to_anchor=(1.4,0.5))

<matplotlib.legend.Legend at 0x22b3ff5e910>

fig,ax=plt.subplots()
ax.scatter(bestModels['classifier'].unique(),bestModels['avgRecall'].unique(),label='smote')
ax.scatter(bestModelsNo['classifier'].unique(),bestModelsNo['avgRecall'].unique(),label='no smote')
ax.scatter(bestModelsM['classifier'].unique(),bestModelsM['avgRecall'].unique(),label='msmote')
ax.tick_params(rotation=90)
ax.set(title='Precision/Recall for Models with best Accuracy')
ax.legend()

<matplotlib.legend.Legend at 0x22b40793e20>

fig,ax=plt.subplots()
ax.scatter(bestModels['classifier'].unique(),bestModels['avgF1'].unique(),label='smote')
ax.scatter(bestModelsNo['classifier'].unique(),bestModelsNo['avgF1'].unique(),label='no smote')
ax.scatter(bestModelsM['classifier'].unique(),bestModelsM['avgF1'].unique(),label='msmote')
ax.tick_params(rotation=90)
ax.set(title='F1 for Models with best Accuracy')
ax.legend()

<matplotlib.legend.Legend at 0x22b4071c2e0>

fig,ax=plt.subplots()
for classifier in modelCompare['classifier'].unique():
    subdf = modelCompare[modelCompare['classifier']==classifier]
    ax.scatter(subdf['avgAccuracy'],subdf['avgF1'],label=classifier)
ax.set(xlabel='Accuracy',ylabel='F1',title='Each point is the Average of 5 fold Runs for each algorithm at a specific feature set/parameter set')
ax.legend(bbox_to_anchor=(1.4,0.5))

<matplotlib.legend.Legend at 0x22b408d8eb0>

classifiers = list(bestModels['classifier'].unique())
f1s         = list(bestModels['avgPrecision'].astype(float).unique())
classifiers2 = list(bestModelsNo['classifier'].unique())
f1s2         = list(bestModelsNo['avgPrecision'].astype(float).unique())
classifiers3 = list(bestModelsM['classifier'].unique())
f1s3         = list(bestModelsM['avgPrecision'].astype(float).unique())
fig,ax=plt.subplots()
ax.scatter(classifiers,f1s,label='smote')
ax.scatter(classifiers2,f1s2,label='no smote')
ax.scatter(classifiers3,f1s3,label='msmote')
ax.tick_params(rotation=90)
ax.set(title='Precision for Models with best Accuracy')
ax.legend()

<matplotlib.legend.Legend at 0x22b41fe1850>

classifiers = list(bestModels['classifier'].unique())
f1s         = list(bestModels['avgAccuracy'].astype(float).unique())
classifiers2 = list(bestModelsNo['classifier'].unique())
f1s2         = list(bestModelsNo['avgAccuracy'].astype(float).unique())
classifiers3 = list(bestModelsM['classifier'].unique())
f1s3         = list(bestModelsM['avgAccuracy'].astype(float).unique())
fig,ax=plt.subplots()
ax.scatter(classifiers,f1s,label='smote')
ax.scatter(classifiers2,f1s2,label='no smote')
ax.scatter(classifiers3,f1s3,label='msmote')
ax.tick_params(rotation=90)
ax.set(title='Best Accuracy for each Model')
ax.legend(bbox_to_anchor=(1.4,0.5))

<matplotlib.legend.Legend at 0x22b4203c9a0>

bestRf = pd.merge( modelCompare,
modelCompare[modelCompare['classifier']=='RandomForestClassifier'].groupby(['smote','classifier'])['avgAccuracy'].max().reset_index(),
on = ['classifier','avgAccuracy'])

fig,ax= plt.subplots()

ax.scatter(bestRf['smote_x'],bestRf['avgF1'],label='f1')
ax.scatter(bestRf['smote_x'],bestRf['avgRecall']+0.001,label='recall')
ax.scatter(bestRf['smote_x'],bestRf['avgPrecision'],label='precision')
ax.scatter(bestRf['smote_x'],bestRf['avgAccuracy'],label='accuracy')
ax.set(ylabel='metric value')
ax.legend(bbox_to_anchor=(1.4,0.5))
ax.set(ylim=[0.5,1])
ax.set(title='Best SMOTE vs Best No Smote Models for Random Forest (the best out of all models)')

[Text(0.5, 1.0, 'Best SMOTE vs Best No Smote Models for Random Forest (the best out of all models)')]

bestRf

	classifier	avgAccuracy	avgF1	avgPrecision	avgRecall	smote_x	smote_y
0	RandomForestClassifier	0.781981	0.797991	0.781981	0.781981	smote	smote
1	RandomForestClassifier	0.757655	0.738540	0.757655	0.757655	no smote	no smote
2	RandomForestClassifier	0.988380	0.989054	0.988380	0.988380	msmote	msmote
3	RandomForestClassifier	0.988380	0.989047	0.988380	0.988380	msmote	msmote

'''

acc          
recall
f1
precision

'''

'\n\nacc          \nrecall\nf1\nprecision\n\n'

fig,ax=plt.subplots()
ax.barh(['accuracy','f1','recall','precision'],
        [0.781981, 0.797991, 0.781981, 0.781981], label='smote')
ax.set(xlim=[0.7,0.9])

[(0.7, 0.9)]

fig,ax= plt.subplots()
ax.barh(['accuracy','f1','recall','precision'],
        [0.757655, 0.738540, 0.757655, 0.757655], label='no smote')
ax.set(xlim=[0.7, 0.9])

[(0.7, 0.9)]

fig,ax= plt.subplots()
ax.barh(['accuracy','f1','recall','precision'],
        [0.988380, 0.989054, 0.988380, 0.988380], label='msmote')
ax.set(xlim=[0.7, 0.9])

[(0.7, 0.9)]

Statistics

Visualizations

Discussion

Conclusions